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GUIDE TO BIG DATA

INTRODUCTION P3

SOFTWARE FRAMEWORKS THE CORE OF BIG DATA P4

RECOMMENDATION ENGINES P5

CHOOSING THE RIGHT BUSINESS INTELLIGENCE TOOL P6

REAL-TIME DATA CAPTURE FOR BIG DATA P7

BIG DATA FOR SMB RETAIL P8

BIG DATA IN TRAVEL P9

OUTSOURCING YOUR BIG DATA REQUIREMENTS P10

COMPANY PROFILES P11

NOTE FROM MDEC P12

PART 1 - CONTENTS:

GUIDE TO BIG DATA

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We were really excited to collaborate with the Multimedia Development Corporation (MDeC) to write and publish this Data & Storage Asean’s Guide to Big Data.

Having the chance to work with multiple smaller technology companies from Malaysia has been a real education and has enabled us to produce a guide that is more unique and varied in content.

Big Data is an evolving discipline with many emerging technologies. It’s a time of technical evolution.

Typically at such a stage in the IT cycle, the really exciting innovation happens in smaller independent technical companies. Smaller companies sometimes get consumed by larger MNCs and if they produce something “hot” they may become MNCs themselves.

By working with specialist local companies, we have been able to explore and explain the key areas of Big Data, and do so with expert guidance and input from technologists developing cutting edge technologies that push the

boundaries of areas like Neuronal Network Databases, ecommendation Engines and Data Capture.

Our thanks go to MDeC for upporting this guide and linking us with MSC Malaysia status companies to create a truly collaborative and informative guide.

Yours in Data & Storage Allan Guiam - Editor Data&StorageASEAN

Yours in Data & Storage Allan Guiam - Editor Data&StorageASEAN

INTRODUCTION FROM THE EDITOR

NOTE FROM MDEC CEO – DATO’ YASMIN MAHMOOD

It is indeed a pleasure for me to pen a few words in the 2nd edition of the Data & StorageAsean’s Guide to Big Data in collaboration with Data & Storage ASEAN. I am sure this extended guide will serve as a good reference to industry players as it contains comprehensive information on Big Data Analytics.

The Big Data sector is booming. IT analysts worldwide have predicted that more companies and organisations will seek to leverage on insights and power of big data analytics to chart their vision and strategies. The Big Data Analytics (BDA) segment presents diverse opportunities that requires immediate attention. Malaysia has already started on its BDA journey and the potential revenue from it is estimated to be about RM0.72 billion by year 2020.

The Multimedia Development Corporation (MDeC) has taken steps to accelerate the adoption of Big Data Analytics (BDA) among Malaysian companies by establishing a network of

BDA Innovation Centres of Excellence. The initiative involves bringing together private and public entities which would act as conduits to build critical mass in BDA adoption and innovation. It is also part of MDeC’s aim to turn Malaysia into a BDA hub in Asean.

Beyond driving the BDA capacity and adoption amongst Malaysian businesses and organisations, this initiative will also allow us to develop our nation’s talent into a strong pool of data scientsts. This will ultimately result in the creation of Malaysian talents who are highly proficient knowledge workers in various economic sectors and industries with IT ompetencies at the core.

GUIDE TO BIG DATA

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If you have been researching Big Data, you will no doubt have heard of Hadoop - the popular software framework for storing and processing Big Data.

But what is Hadoop? Is it the only emerg-ing platform for processing Big Data? Are there other alternative technologies that may be better suited to Big Data tasks?

Hadoop or more formally referred to as Apache Hadoop was originally developed out of papers published by Google that described its distributed file system and a process called MapReduce. Without getting too deep into the technology, MapReduce solves the problem of indexing millions or billions of data items.

Hadoop is built on a clustered computing environment where data is stored against multiple nodes running commodity hardware linked through a network. Because processing is shared, as more processors and storage are added into the cluster, MapReduce is able to perform fast analysis on huge data sets.

Whilst Hadoop is arguably the most famous framework, there are other technologies, which are viable alternatives to Hadoop such as Disco (originally developed by Nokia) also based on MapReduce, and NoSQL databases, such as MongoDB, NoSQL and Oracle NoSQL.

The challenge of Big Data is not only in its scale, but also in how we might want to analyse it. We need to be able to capture the data and store it in a way that allows flexibility in how we can access and utilise it. Consequently, the software frameworks used to handle Big Data will be varied and

continue to grow in number.

Our company, Neuramatix, developed a patented technology called NeuraBASE which creates a datastore that emulates the way, we believe, the human brain works. Taking this neuronal networking approach allows us to process enormous amounts of data at high speed without the need for distributed clustered computing.

The NeuraBASE datastore is built based on a parent-child dependency architecture. As a simplified example, the parent data or node might be the letters C, A and T. The child data or node created from this may be the words CAT, ACT and AT. These words will not be stored as separate entities, they are created from pointers and dependencies to the parent node.

This approach has two major unique factors that are perfect for Big Data. Firstly, the more data we ingest, the smaller the rate of growth will be in NeuraBASE. This keeps the data processes manageable without having to move to distributed computing models. Secondly, as we ingest more data, more dependencies are learned, meaning, allowing the data model to perform tasks learned by recalling relevant dependencies at high speed. For example, the more bilingual text we input into our machine translation system, the more it improves its translation accuracy - with no further programming required.

The one source of Big Data that exceeds all others is genomics. In genomics research, the NeuraBASE approach we take allows us to search across entire human genome significantly faster than any other methods that employ clustered computing approaches to Big Data.

A detailed description of the Neuronal Networking Approach to Big Data is available here - http://www.neuramatix.com/ANeuronalnetworkapproachofex-pressingnetworkmotifs.pdf

The NeuraBASE approach to Big Data allows us to push the boundaries of artificial intelligence by using a neuronal model that learns and adapts as opposed to rigidly following pre-determined pro-gramming logic and decisions trees. For example, NeuraBASE can be used to enable a robot to learn to self-balance and walk on different terrains. Minimal pro-gramming rules are required as the robot learns from both its successes and failures. Two robots using NeuraBASE in different environments may learn at different rates and in different ways. As they continue to learn and adapt to each of their environ-ment, the eventual style and length of their strides may end up being different, much like how we humans are able learn and adapt to our environments.

We are only scratching the surface of what can be achieved with Big Data. Innovation is happening everywhere. Big Data should not only be about standardised platforms and architecture for problems we face today. It’s about creating technologies that will solve problems we will face tomorrow.

Whilst technologies like Hadoop may be grabbing the headlines today, companies and organisations looking to achieve extraordinary things should look beyond the large global players. If anything, Big Data teaches us about openness to possibilities.

SOFTWARE FRAMEWORKS - THE CORE OF BIG DATA BY ROBERT HERCUS

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ROBERT HERCUS Robert has over 40 years’ experience in Information Science, specialising in large-scale computing infrastructure and computationally intensive projects. This includes

hardware and software development, military systems development, overseeing implementation of the IT infrastructure and development of the Touch ‘n Go prepaid card in Malaysia.

Robert is the co-founder of the Neuramatix Group of Companies and the inventor of NeuraBASE,

a patented concept for the construction of neuronal networks using temporal or spatial association of neurons. He is also the Managing Director and co-founder of Malaysian Genomics Resource Centre Berhad (MGRC), one of Asia’s leading providers of genome sequencing and analysis, and genetic screening services.

GUIDE TO BIG DATA

If you are an Amazon customer it’s more than likely that you have been the beneficiary of one of the most successful and advanced recommendation engines around today. When you buy books on Amazon you will have noticed the recommendation that “people who purchased this book also purchased that book”. Reportedly 35 percent of Ama-zon’s business is generated from recom-mendations.

Increasingly more business is conducted online. Consumers’ online behaviour and footprints are getting bigger and more detailed. With Big Data technology this behaviour can be collected and analysed in order to make customised and indi-vidual predictive recommendations for complementary purchases.

In the early days of online retailing a one-size fits all approach largely based on “tags” or “hard linking” product depend-encies was considered effective. To this day these simplistic types of recommen-dations engines still have a part to play for ecommerce sites selling a simple array of goods.

However today we are seeing more businesses including ecommerce sites like Amazon employ more advanced ways to customise the consumer recommenda-tion experience – an approach that is increasingly not just important but vital.

Today, building a recommendation engine is a true exercise in Big Data collection

and predictive analytics. Significant real-time analysis needs to occur without impacting website performance.

For each person that visits a site, every action they perform on that site needs to collected including personal (if available), geographic and product information. Other factors such as seasonal variations and special opening hours also need to be included in the data collection process. Following which all data collected needs to be matched and analysed.

As recommendation engines evolve to pull in and assess all of this data, two main models have stood out from the rest:

Content filtering which is based on linking keywords and values in user profiles and product descriptions; and

Collaborative filtering is based on analysing large amounts of user behav-iour, actions, responses and preferences in order to make predictions about their likes based on matching to similar users.

More recently, we have also seen the development of Hybrid Recommender Engines, where both content and collabo-rative filtering are deployed in a single solution. Research shows that for more complex buying processes a hybrid approach can result in more accurate and effective recommendations.

At Predictry my team is working on developing recommendations even further. We are incorporating a third area into our hybrid recommendation engine

which we term social sentiment. This pulls data from social media, specifically data which expresses a sentiment such as “comments” or “likes”. We combine this with content and collaborative analysis to create very highly targeted, customised and individualised recommendations.

Typically this technology is being used for upselling and cross-selling as part of the ecommerce process. However the uses could extend far beyond that, potentially giving you a totally individualised web experience no matter what you are searching for.

In conclusion, Big Data and the technolo-gies that support it are enabling us to create recommendation engines which truly filter the “noise” on the internet and bring you directly to the items and content that you want to see. At Predictry we believe we are at the forefront of individu-alising customisation. However, traditional and established methods may still be appropriate for some applications.

When looking at adding recommendation to your e-business or e-service, the most important thing is to understand the complexity of your offering as well as the profile of your user base. Once you have a strong understanding of those factors, only then can you make the right choice of recommendation engine and provider.

RECOMMENDATION ENGINES BY ST CHUA

ST CHUA, PREDICTRY CEO ST enjoys turning ideas to reality. His experience includes being the Global Business Developer of Rebate Networks, a German-based Venture Capital with interest in the

daily-deal space spanning across 30 countries globally. Before that, he was an integral part of Maxis’ CEO office where he was heavily involved in new business and overseas expansion, including

M&A deals worth USD1.3 billion. His role was expanded to become the retail project manager for Maxis, managing 29 retail outlets nationwide in Malaysia. Besides being a Director in Verve Technologies Sdn Bhd, he is also a co-founder of a health spa, a FMCG distribution company, a women fashion e-commerce site, a professional photo studio and a market entry consultant. In his free time, he also mentors European and Russian based start-ups. ST holds an MBA from INSEAD, France.

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Business Intelligence (BI) has been around for many years even before the buzz started around the term Big Data. BI is Data Analytics, and for years, BI tools have served the purpose of enabling businesses to pull data from various sources into one analytical engine. Permitting data to be sliced and diced in ways previously not possible with traditional Relational Databases.

In essence this is a large part of what Big Data is all about – taking huge amounts of raw data and turning that into something useful for business. The challenges of doing this have evolved with massive data sets needing to be collected from increasingly varied sources. Whilst BI is a mature market with established players, the technology around Big Data Analytics is still evolving.

As with all new and evolving technologies, we caution customers not to get caught up in the hype when selecting their BI tool. The most important thing is that you choose a solution and a provider that solves YOUR problems.

Before choosing your BI tool, it is impor-tant to think about the data you need to ingest and how easy or difficult that task will be with different tools. You also need to consider how regimented or flexible you plan will be based on the variety and type of data you expect to analyse. These factors will affect the technology you use.

Today there are a number of preferred models for BI engines.

One of the most mature models is based on Relational Online Analytical Processing (ROLAP). ROLAP uses data already pre-indexed data from the RDBMS from

which it is pulling data. This usually means that load times can be fast. But as it relies on “pre-indexed” data, ROLAP is not always as flexible in how it can analyse data. If you have tightly defined analysis for whch SQL type queries are well suited, then ROLAP can be the correct choice. ROLAP is best for analysing non-aggregatable data such as textual strings. However when it comes to Big Data, ROLAP based BI tools may often be too reliant on RDBMS indexing to easily and effectively deal with unstruc-tured data. Also, because ROLAP is based on SQL type querying it can suffer from relatively slow query performance.

Another often used model is Multidimen-sional Online Analytical Processing (MOLAP). MOLAP tends to be built on a proprietary engine and uses a concept called pre-aggregation, which means the calculations are pre-generated as the datastore is created. The advantage is that highly complex queries can be run very quickly. The flexibility and speed makes it excellent for dealing with many of the demands of unstructured Big Data. However there are limitations. Mainly due to the pre-aggregation process, loading data can be complex and may also need extra investment in skilled resources. In addition, this method of building the datastore can place limitations on scalability. MOLAP is more suited for analysing summary data from larger data sets.

Big Data puts new demands on BI and Data Analytics. Raw data now comes from so many sources and there is an increasing need to perform BI in real-time, so we have to advance BI methodology to

keep pace with evolving demands. We are seeing Agile Business Intelligence in response to the ever evolving questions we may want to ask based on expanding data sources.

At Speedminer we have developed what we call a columnar approach to BI. We use an underlying object orientated database to import data from nearly any source whether structured or unstruc-tured. This approach enables us to break the data down into a format that is both scalable and flexible, in many cases giving us the benefit of both MOLAP and ROLAP. Our approach also means that applications can be implemented on our database enabling data to be available to our BI engine the instant it is created. We believe this is unique and enables true real-time BI analytics. Our Columnar approach is highly flexible and adding new data sources into the BI engine is simple and fast.

BI tools deployed correctly will save time on existing business analytical tasks. For instance, our Columnar approach has enabled a government department to significantly reduce a monthly number crunching exercise from 13 days to 1 ½ days.

To be clear, there is no obvious right choice. You need to understand your data, set your criteria and make decisions based on your objectives. Is it speed of load, ease of load, speed of query, or flexibility of query? Once you know your priority you can start to review your options based on an understanding of which methods are best suited to your needs.

CHOOSING THE RIGHT BUSINESS INTELLIGENCE TOOL BY THOMAS HOW

THOMAS HOW Thomas How, is the founder of Speedminer Sdn. Bhd. He has more than 20 years of IT experience especially in consultation, development and implementation of Data

Warehouse and Business Intelligence (BI) solutions. He has in-depth experience utilising efficient, scalable techniques dealing with large-scale data

warehouses across a variety of industries including customers such as the Department of Statistics Malaysia (DOSM), MATRADE and Celcom (M) Berhad. His experience with different customers’ requirements, architectures, and methodologies has enabled him to evolve a unique approach to data warehousing utilising best of breed components and methods. He actively works on data warehouse implementation and consults internationally.

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There was a time decades ago when starting a new business, all you needed was good products and friendly neighbourhood customer service. These days the hyper competitiveness of local business environments re-quires more than a great product or superb customer service. It requires business intelligence that is dynamic and real-time reflective of the target market. Companies that have access to the right information and are able to act upon these have the upper hand.

Market intelligence has been around for years and while the fundamentals have remained unchanged, the demand for greater scale and the ability to amalga-mate the data, and act on the information has certainly challenged marketers’ abilities to deliver.

Core capabilities and differentiator

Raydar Research is a marketing informa-tion services and research agency. Our core competency is around data collec-tion. We developed software and mobile solutions to allow for large scale data collection, the results of which can be used to help an organisation bridge the gap between consumer expectations and businesses deliverables resulting in performance improvement, satisfaction and loyalty. We have partnered with local carriers to identify the target demograph-ics and use their mobile devices to engage the audience and develop real-time market intelligence.

Our key differentiators include the ability to identify or define a very targeted group

in terms of demographics, the ability to collect the data at the point of engage-ment as it happens, and the ability to provide instantaneous data analysis, which in turn, allows organisations to make business decisions faster and in real-time. Many of our clients find the ability to close a market intelligence project faster as a strategic enabler allowing them to execute targeted campaigns faster, more efficiently.

Most of our clients are from overseas markets like Singapore and other markets around the region. By partnering with local telco carriers, we are able to conduct location-based surveys using the users’ mobile device to really hone in on specific users – for example, travellers at the Changi Airport in Singapore or perhaps shoppers on Orchard Road.

Learning Experience

Having worked with so many organisa-tions over the years, providing advice as well as developing innovative processes and technologies, it is interesting to discover the differences and similarities of our engagements over the years. Busi-nesses looking to harness market research for the first time must take a moment to understand their customer’s profile, particularly for startups or organi-sations strapped for resources. The advice of starting small will allow the business to focus its energy and resourc-es, and hopefully help establish a beach-head market that it can build from. Use highly targeted research, identifying the addressable market, and develop a

persona for the organisation. One thing is certain you cannot establish a position in your target market sitting in a desk. Market research is as much a discipline as it is a practice. We suggest organisa-tions to pick a reliable data collection company to partner with for field work. Ask for credentials and used cases. Take time to ask the service provider making sure they understand your business and your industry.

The Future

Market research as a business practice is beginning to draw interest among Malaysian businesses. Unfortunately, many do not understand or know how to use market research can help them build strategy. Coupled with digital and social media, there is an opportunity for local companies to draw upon the success and experience of businesses in other countries to hone and harness the potential.

What is also needed is for industry associations and relevant government bodies to rally around these innovations and educate members and the general public. Together relevant bodies need to dig deeper into how the technology can serve the interest of their members so that the industry, as a whole, is able to benefit from the potential of market research. With overseas businesses coming into Asia and regional players expanding into Malaysia, there is ample drive and opportunity for harness the potential of market research.

REAL-TIME DATA CAPTURE FOR BIG DATA BY KYM WONG

KYM WONG Kym Wong is the founder of Raydar Research, the creator of multiple mobile platforms to collect Big Data. He has a knack for translating real business needs into mobile applications that deliver value to customers and businesses such as banking, healthcare, manufacturing and consumer goods. www.raydarresearch.com

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S i m p l i f y i n g G r o w t h

Ranked 13 in the 2013 Global Retail Development Index report by management consultant A.T. Kearney, Malaysia is forecasted to experience solid retail growth over the coming years. Retail sales are expected to pick up following government initiative to improve the retail despite concerns over higher operating costs.

We believe these challenges can easily be overcome by better understanding customer buying behavior. Web Bytes is one of the early pioneers of online retail management solutions – essentially hybrid point of sales (POS) systems that combine advance technology, proprietary software and cloud computing to capture and analyse customer buying patterns.

Retailers have a micro view of their business, i.e., they know what products sell well in a specific store or mall. But beyond this, they do not understand why certain products sell at specific periods in the year. What we do at Web Bytes is aggregate the retail sales data to draw a picture of customer buying behaviors over any period of time at any area in Greater Kuala Lumpur.

Analytics is still at its very nascent stage within Malaysia’s retail sector. Many SMB retailers make decision using only their gut feeling. For more than three years, we’ve been serving SMB retailers – most of whom are not very analytics savvy. We give them the tools to analyse their business data in much the same way larger retail chains perform business intelligence to discover

what products sell and the margins they make selling goods.

What is missing here is the ability to see the whole industry. For example what products sell well in Suria KLCC in January versus Bukit Bintang. Or why people flock to Bangsar district. Imagine if a retailer has access to data that shows what products move during January in MidValley this information would alter the way retailers stock products.

Like other SMBs, retailers are very con-servative when it comes to investing in technology. One of the best things about our solution is that we are fully on the cloud. We fully support a pay per use model. Many of our SMB customers often start with simple offline POS systems. Over time as the business grows, we can scale our backend to support their business.

We do so by ensuring that we support and connect with standards-compliant POS infrastructure. You only need to install a client program to handle the peripheral. We developed an in-house application that is installed at retailer POS.

Today our customers include fruit stalls, apparel, footwear and grocery stores. Come 2015 when the government intro-duces a goods and services tax (GST), our customers will be comforted to know that our systems will comply with the new tax system on day one. That cannot be said of many of today’s current systems.

Does having a business analytics or business intelligence (BI) constitute having

a Big Data strategy?

That is a misconception. People think that just because they have deployed a BI solution they now have Big Data. In our view, true Big Data is having access to information beyond your business. A single retailer can only see what is happening at their store. If we are able to extend that knowledge to encompass the entire industry – that is Big Data!

Today we process a billion Ringgit of business annually. Does that give us Big Data? Absolutely not! We are working to rebuild our systems to accommodate the Big Data. As a vendor and an industry, we face a number of challenges including adopting standards for how data is created, collected, analyzed, managed and destroyed. We are not yet there but certainly we are getting there.

As with all young technologies, another key challenge is educating our retail customers about data security and privacy. Two years ago we achieved ISO certification and this has helped customers understand that the service we provide is secure – that we do not access the details of the data, merely aggregate the data to allow create a picture of the industry. This gives our customers the confidence that their data remains private and secure. But for Big Data to become widely accepted and used, we need industry and government support to qualify and certify technologies and standards.

BIG DATA FOR SMB RETAIL BY BOON-SHENG OOI

OOI BOON SHENG Ooi Boon Sheng, Founder of Web Bytes Sdn. Bhd., From age 18 Boon Sheng has show entrepreneurship starting as a freelance programmer. Later he obtained his Bachelor

Degree of Computer Science from Universiti Sains Malaysia (USM) and achieved the USM Gold Medal Award by Harvard Foundation for academic excellence. Whilst at University Boon Sheng designed an engineered and Resources Management Tools (RMT), which won several

awards including the Gold Medal award at ITEX07 and Gold Medal at the British Innovation and Technology Show, UK 2007.

More recently Boon Sheng formed Web Bytes, a software technology company that deliver cloud-based solution for the retail industry in the region. Web Bytes’s anchor product, Xilnex, currently powers thousands of retail users in over a thousand outlets. The solution, powered by Microsoft Azure, processes over RM 1 billion live retail transactions annually for retail businesses across Malaysia, Singapore, Australia and Cambodia.

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According to the 2013/2014 ITB World Travel Report over 5.3 million Malaysians travelled overseas spending US$7.2billion in 2012. In the same year Malaysia welcomed 25 million tourists contributing RM60.6 billion to the economy according to the UNWTO. The Travel & Tourism indus-try generated US$50.3 billion to the local economy (over 16 percent of total GDP) and is forecasted to reach US$54 billion in 2014.

The challenge for everyone in the industry is to figure out which parts of the country locals and foreign tourists will want to visit, and the goods and services they are willing to spend on. For many businesses, speculations are ripe that Big Data may hold the key to unlocking the puzzle within the industry.

The operative word is ‘speculation’ for indeed whilst many businesses have heard of Big Data and are interested to use Big Data, many don’t know how to deploy and use Big Data to their advantage. For most the knowledge of Big Data is limited to reading materials and snippets of informa-tion shared behind seminar walls. Indeed when meeting interested parties, the most common approach we encounter is “I read about it. My company has strong direction to harness Big Data but we don’t know to do it.”

As an early proponent of Big Data, we help them explore the potential of the technol-ogy and at the same time help them recognize that Big Data is a transformative journey that requires making big, some-times, disruptive decisions of they are to achieve their Big Data objectives.

The reality of Big Data is that it forces you to wrestle with three key strategic and operational challenges: information strategy, data analytics and enterprise

information management. Information strategy revolves around how you harness the information at your fingertips. Data ana-lytics is about garnering insights from your data so you can predict future customer behaviour, trends and outcomes. Finally, because of the volume, variety and velocity of data coming into your systems, you need an enterprise information manage-ment to drive innovation.

Experienced data analytics people will tell you that Big Data is complex technology that requires complex solutions. It is complex because in one single system you have congregations of large volumes of different types of data coming in very rapid sequence, and changing just as quickly. To handle this complexity therefore requires complex but powerful and highly scalable platforms like Hadoop. 

At Fusionex, we live by the principles of simplicity. The many failed ERP and CRM systems have taught us that users will shy away from using tools too difficult to use. Conversely we saw from the success of the Apple iOS platform that users will flock towards technology that is easy to use. We recognised the capability of Hadoop to allow us to work with Big Data with minimal programming. We developed GIANT – a Big Data analytics software to shield end-users from the complexities surround-ing Big Data, low-level plumbing, hard-core Apache Hadoop and MapReduce program-ming.

We are able to do this because we work with some of the largest retailers, hyper-markets and malls to connect their transac-tional data and provide them insight on customer behaviour. We also work with some of the largest hotels to help them identify customers who are buying or not buying their promotions and developing

insights to drive future campaigns by clustering customer behaviour patterns. 

Many large enterprises are unfased by complex technologies. For instance in the travel industry, organizations already have structured data culled from CRM systems. They also have unstructured data captured from customer engagements within their call centre. The challenge is how to combine all these data to develop a 360 degree view of the customer. Many within the travel industry continue to struggle to fully understand customers proactively. They often operate in reactive mode waiting for customers to approach them. Most marketing campaigns are broadcast mode designed to cast a wide net hoping to make a few catches. They don’t have clear view of customers or even an adequate cluster of customers.

The reality is that because Big Data is still in its infancy, many businesses lack the skillset, exposure and technical expertise to deploy Big Data. Many are also turned off by the upfront costs that come with building and deploying an in-house Big Data systems.

Marketers of Big Data principles of speak of the three Vs of Big Data: volume, velocity and variety. We believe that for businesses to truly reap the benefits of Big Data, they need to aim for a fourth V – val-ue.

For decades companies have been building repositories of data that let them see what happened in the past. But looking at historical data does not allow them to predict the future. What they want is to be able to predict what the customer will buy in the future. That for them is a powerful value. Big Data promises to make that happen.

BIG DATA FOR TRAVEL BY ISAAC JACOB

ISAAC JACOB As Vice President of Business Consulting, Isaac Jacob has more than a decade’s experience in functional consultancy and enterprise software project implementations.

Specialising in process re-engineering and change management, he has implemented Business Intelligence and analytics projects in various

industries, involving large volumes of data, different data sources to provide in depth analysis of data and trends. 

Jacob’s technical background coupled with his strong accumulated domain knowledge across manufacturing, market research, financial and asset management has led him to successfully execute and spearhead enterprise projects globally spanning across countries such as the U.S, Singapore, Malaysia, Holland, France, Hong Kong and U.K.

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The hype around Big Data has got many businesses believing that Big Data is the “holy grail” in their pursuits of things such higher revenues, improved customer loyalty and business expansion. Most businesses want to get on the bandwagon and see what Big Data can do for them.

The problem is that Big Data is more than buying a Business Intelligence (BI) tool and running some reports. In truth the investment required to do Big Data properly is significant. In the same way the thought process and planning required for any Big Data initiative are also significant.

Outsourcing Big Data is a very viable option that almost any company considering working in this area should consider. There are some specific situations where outsourcing is not possible, usually this revolves around privacy and confidential information, but beyond this using an Outsource Partner may very well be the best option for deriving value from Big Data.

The main benefit of outsourcing to a Big Data specialist is expertise. As an example at Pulse Group, in our Big Data practice “Pulsate” we have a combined 10 years of experience in this field which becomes an immediate head start for companies new to Big Data that employ our services.

The starting point with an outsource partner is also beneficial in its own right. Before we can start we need a tightly defined OBJECTIVE of what you want to achieve from your Big Data project. We have seen in-house Big Data projects fail simply because the aims and objectives were too loose from the outset. A reputable outsource partner will help you set those objectives. Just as important they should be able to help you assess whether those objectives are achievable. Big Data promises so much, it takes experience to know in advance if it can deliver.

A major criterion to getting “into Big Data” is the investment required. Big Data needs to be done properly or not all and it’s not just about hiring an analyst to crunch some numbers. There is investment in new hardware and software, middleware, networking and bandwidth. In addition the technology that you need to invest in may be new to your IT people as an example Hadoop or object based databases. So in addition to capital expenditure there may also be additional human resources required. Companies like Pulse that have years of Big Data experience already have the skills and the technology in place, so our customers benefit from the economies of scale that we already enjoy. For a short term temporary Big Data project outsourcing may be the only viable way to achieve

ROI. When establishing a permanent Big Data practice, this significant investment needs to be factored in and when it is, outsourcing may still be the best option.

At Pulse we see one other huge value that we bring to the success of Big Data initiatives, and in our view it is a major factor in deciding whether to insource or outsource. This is “filtering noise”. Big Data is not just big as data can come from multiple sources and much of the content can be a distraction rather than helpful. Cleaning and selecting the right data to analyse is a crucial but non-trivial task. Getting it wrong is almost certainly setting you up to fail. So in some respects it is ironic that to work with Big Data you need to know Big Data to start with. In our experience you either need to buy in the experience and expertise or outsource it.

Outsourcing Big Data initiatives is not for everyone! Outsource companies will generally have broad experience. However focused vertical experience of a fully resourced in-house team is likely to be more attuned to very specific needs of a particular vertical.

The point to note is that to undertake a Big Data project is a serious undertaking that will present difficult challenges, steep learning curves and investment of time and money. Outsourcing these initiatives should always be on the table as an option for any new Big Data project.

OUTSOURCING BIG DATA BY BOB CHUA

MR. BOB CHUA As CEO and Executive Chairman, Pulse Group PLC, Bob Chua is a Malaysian entrepreneur running Asia’s premier Marketing Analytics and Big Data Solutions Provider. He is the proud winner of many entrepreneurial awards,

including the prestigious Ernst & Young Entrepreneur Award in 2008.

Bob advises companies on various public and private boards, and enjoys mentoring budding entrepreneurs in his spare time.

bob.chua@pulse-group.com Skype ID: bobchua

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COMPANY PROFILESThe NeuraBASE Toolbox is a commercial software library for developing intelligent systems and devices based on a neuronal network model. The NeuraBASE Toolbox functions enable users to create intelligent applications by understanding the sequences and frequency of events that occur within a dataset. Once NeuraBASE has been trained using a set of data, systems developers can perform analysis and make predictions by detecting similar patterns in other sets of data. A dataset that has been

trained using NeuraBASE can be searched and recalled to better understand the conditions or sequences of events which led to the successful achievement of a task. This can help developers to easily recreate these conditions in their environment. http://www.neuramatix.comTel +603 2283 3860

Speedminer Sdn. Bhd. (Speedminer) is an MSC (Multimedia Super Corridor) Company. Its flagship product - Speedminer System has been successfully implemented at various sites throughout the world. Speedminer works with various Sales Channel/OEM Partners who distribute our software in selected geographies and help our customers tailor and deploy solutions. At the moment, Speedminer’s clientele includes organizations from Asia, Europe, America, Australasia, Middle

East and Africa. Speedminer System has received many awards include MSC-APICTA Award 2006-Best of Applications And Infrastructure Tool, PIKOM Awards 2006/2007- Emerging Company of The Year and the Best Product of the Year. Speedminer Sdn Bhd is a recipient of MSC Malayia’s Innovation Voucher.http://www.speedminer.cominfo@speedminer.com

Web Bytes’s anchor product, Xilnex is a new-age Cloud-Based Retail Management Solution which helps retailer to grow without having to deal with the complexity and price of a conventional solution. Xilnex is one of the few retail management solutions in the world that is EAL1 (Common Criteria/ISO 15408) certified which promises world class security framework in place so that retailers can operate without worrying on its

data security and reliability. Xilnex currently power thousands of live Point-Of-Sales terminals which process over RM 1 billion of sales transactions a year. Web Bytes Sdn Bhd is a recipient of MSC Malaysia’s Innovation Voucher.http://www.xilnex.comsales@xilnex.com

Pulse Group Plc, is a research process outsourcing group, providing a range of online and offline solutions to the market research industry.We provide a range of services, including online market research panels, call centre solutions, translation services, and qualitative online and offline solutions.Our complete research solutions integrate seamlessly with your internal systems and processes, allowing you to stay focused in delivering value to your clients.As a virtual extension to your business, our services provide you with the confidence that allows your business to focus on:

• Delivering value to your clients• Transfer fixed costs into an on-demand cost model• Facilitate your business expansion with minimal riskWith an experienced global team, we are able to provide our clients with timely, high quality data and importantly value for money. With leading technology in call-centre support, Pulse Group Plc. offers a one-stop solution.http://www.pulse-group.cominfo@pulse-group.com

Predictry is the big data arm of Verve Technologies Sdn Bhd that is focussed in the research and development of Predictive Analytics solutions. Its core product is a robust and customisable recommendation engine to meet the latest business needs of e-commerce, marketplace, web-listing or content sites. By having Data Scientist and Business Intelligence experts in the team, Predictry is able to provide customised solutions with the goal of assisting clients to increase relevancy, user

engagement and click-through-rates. Predictry is supported by MDeC and a recipient of the Product Development and Commercialisation Fund (PCF) for Big Data. Verve Technologies Sdn Bhd is a recipient MSC Malaysia’s PCF (Product Development & Commercialisation) Grant.http://www.predictry.comhello@predictry.com

We help companies increase their profitability by providing them with data driven insights to create innovative customer experience solutions that truly delivers value to their customers and results in lasting loyalty.We achieve this by providing our clients with technologies and systems that capture “in-the-moment” experience and streaming those data in

support of our clients’ efforts to build lasting relationships with their customers.http://www.raydarresearch.cominfo@raydarresearch.com

Travel & Hospitality is a core focus for Fusionex, where we have built various solid platforms to assist industry players for the purposes of improving sales revenue, reduce operating costs and raising the bar for customer satisfaction. For early adopters of IT for their businesses, we have created an online presence through services like online booking of products and services, as well as integration with social media channels for an optimised consumer experience.The following are just a few of our

key solution offerings are Online reservation systems and Travel agent booking management systems. Fusionex is a recipient of MGS (MSC Malaysia R&D Grant Scheme) Grant and MSC Malaysia’s PCF (Product Development & Commercialisation) Grant.http://www.adv-fusionex.commy1.info@adv-fusionex.com

S i m p l i f y i n g G r o w t h

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Big Data is a key transformative technology that is being pushed for adoption under the Digital Malaysia Plan, the national initiative to advance the country towards a vibrant digital economy by 2020.

Digital Malaysia will achieve this by creating an ecosystem that promotes the pervasive use of Digital Technology in all aspects of the economy. This will include connecting communities globally and in real-time, in order to increase the nation’s Gross National Income (GNI), enhance productivity and improve standards of living.

Collectively, Digital Malaysia aims to achieve the following: the creation of 160,000 high value jobs, increase Malaysia’s ICT contribution from 9.8% to 17%, provide an additional 1% SME contribution to Gross Domestic Product and create an additional RM7,000 of digital income per annum for 350,000 Citizens.

NOTE FROM MDeC

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MALAYSIA’S ENTREPRENEURIAL ADRENALIN JUNKIE

CARVING A COMPETITIVE FUTURE WITH BUSINESS INTELLIGENCE

FUSIONEX THE ANALYTICS JOURNEY START SMALL THINK BIG SCALE FAST

HOW BIG DATA IS RESHAPING THE FUTURE OF RETAIL

SENSIBLY PREDICTING THE RETAIL BUSINESS OF TOMORROW

SPEEDMINER PREPS MALAYSIANS FOR BIG DATA

TAKING THE PULSE OF A MOBILIZED CUSTOMER

THE CONNECTED RELATIONSHIP BETWEEN IOT AND RFID

THE MANY REAL MARKET OPPORTUNITIES OF BIG DATA

THE SCIENCE AND ART OF BUSINESS INTELLIGENCE – ECEOS STRATEGY

PART 2 - CONTENTS:

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DSA caught up with Pulse Group CEO Bob Chua just after he had returned from a trip to Nepal. Not a business mission, but a thrill seeking ride on old time Royal Enfield Motorbikes across the Himalayas with a couple of adrenalin junkie friends. You can view a video of Bob’s journey here.

Perhaps the most famous entrepreneur adventurer is Richard Branson but there are many others and perhaps we should not be surprised that a thrill-seeking streak runs through these people. Every entrepreneur is a risk taker at heart and their business journeys can be just as “hairy” as their physical adventures.

A look at the history of Chua shows him to be a real “old school” entrepreneur.

After cutting his teeth in senior positions at companies like Neilsen and TNS, Bob felt he had built enough experience in digital research to go it alone, eventually he started Pulse Group, which now lays claim to being one of Asia’s premier Digital research agencies.

Bob’s Pulse Group journey like his Nepal adventure has not been typical. In very short time after founding the company, he successfully took Pulse public in 2008 raising approximately RM2,500,000 on the Plus Stock Exchange in London. By October 2012 Bob and his major shareholders decided that that the shackles of being a PLC were thwarting the development of the company and they made the decision to voluntarily delist.

Doing so has enabled the company to be far more agile and respond to new

opportunities as they come up. Not many Malaysian’s have the drive to list on a London based Exchange and very few, Malaysian or otherwise have the courage to delist. These two facts alone show the extent of Bob’s tenacity.

As one of Malaysia’s early IT entrepreneurs we were interested to see if Bob felt the Malaysian Government does enough to help the new batch of budding start-ups. His view was quite fascinating and very telling. He points out that the Malaysian Government is doing a lot these days to support tech start-ups. A lot more than when he first started out and he sees this as a positive step. However Bob adds a word of caution, he is proud that Pulse has never taken any grants from the Government and points out that too much government spoon feeding is actually a bad thing for an entrepreneur.

This is where his old school heritage comes through. For Bob the struggle to get started is an important part of learning how to survive and excel in the real world. A helping hand from government is OK, but too much and the danger is we create molly-coddled entrepreneurs that don’t have the battle scars to succeed in the commercial rat race.

 Bob’s new Big Data Practice “Pulsate” is further evidence of a “tuned-in” and experienced businessman who knows how to jump on opportunity when it arises.

In truth Big Data is a natural progression for a company like Pulse Group. The business of pulse has always been to extract knowledge from Data.

When Bob started in this business working for companies like Neilson, even though the data collection techniques were different (data was collected by clipboard carrying students being paid to conduct questionnaires in the street) the driving force has always remained constant – extracting value from data.

For a company like Pulse Group, the rise of Big Data can be both a threat and an opportunity, but like all successful entrepreneurs, Bob only sees it as an opportunity. Pulsate his Big Data division is only at the start of its journey, but we wouldn’t be surprised if it drives Pulse Group to greater success than ever before.

It is clear Bob sees the opportunities. Providing outsourced Big Data services is a natural progression of what Pulse Group already does, but we can hear Bob’s brain whirring with the other possibilities he is exploring such as a Big Data training academy to capitalise on the huge forecasted big data skills gap the world is already experiencing.

 We are sure that Pulse Group will have a part to play in the Malaysian Big Data Scene and beyond, but we are even surer that just as Bob is already planning his next Motorbiking Adventure, his entrepreneurial ride is also far from complete.

MALAYSIA’S ENTREPRENEURIAL ADRENALIN JUNKIE WITH BOB CHUA

MR. BOB CHUA As CEO and Executive Chairman, Pulse Group PLC, Bob Chua is a Malaysian entrepreneur running Asia’s premier Marketing Analytics and Big Data Solutions Provider. He is the proud winner of many entrepreneurial awards,

including the prestigious Ernst & Young Entrepreneur Award in 2008.

Bob advises companies on various public and private boards, and enjoys mentoring budding entrepreneurs in his spare time.

bob.chua@pulse-group.com Skype ID: bobchua

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Business intelligence (BI) adoption in Malaysia continues to move forward with Gartner estimating spend on BI to have reached http://www.ftms.edu.my/journals/IJISE/Journal/An%20Empirical%20Analysis%20on%20Business%20Intelligence%20Maturity%20in%20Malaysian%20Organizations.pdf. As with their counterparts in other countries, Malaysian businesses view BI tools are helping them improve decision making by putting information to better use.

One such company at the forefront of helping local and regional companies adopt and utilize BI tool to their potential is Datamicron Systems Sdn Bhd. Data&StorageAsean spoke with Mr. Jimmy Ting Heng Toon, co-founder and managing director of Datamicron on the history of the company and its role in the development of BI and big data in Malaysia.

DSA: Datamicron is now 12 years old, how have things changed for the company since its founding in 2002?

Back when we started Datamicron business intelligence and data warehousing were not commonly understood outside of large enterprises and multinational companies. Big Data, as a concept didn’t exist at the time. It was very challenging trying to convince of the benefits of business intelligence. Over the last 15 years, it’s been an interesting journey.

DSA: Has Big Data always a goal for the company?

Not really! At the time when we started there was no Big Data and social media wasn’t really prominent at the time until about 10 years ago. Big Data itself has only risen to prominence in the last five years. So during those times, big data wasn’t really a goal for us. But over the years as we saw the interest and

opportunities pick up around big data, we decided to join the foray.

DSA: Do you find your customers confused between business intelligence and big data?

It is very true that today there is a lot of confusion and misconception about what big data is about. Some equate big data primarily to large volumes of structured data. The interpretation is not so clear. Whilst the definition of big data in terms of volume, velocity, variety of type and source is consistent, how this is interpreted by the business, and in some cases, the individual is inconsistent. Some people don’t know what to do with big data. Some are using it only for sentiment analysis for example. Some verticals have started collecting machine data but much of this is for future references with little or no action being undertaken today.

In Malaysia, not many organizations are aware of what big data technology is but in many cases they are not actively rolling out big data solutions. I don’t there are many Hadoop installations locally. Many are likely in the initial stages of business intelligence or data warehouse. We are a long way from seeing big data implementations in a meaning full way.

DSA: What are the real world challenges business people have with regards to understanding big data, separating reality from hype, and discerning what big data means for their business?

Business users are keen on big data but they prefer to use packaged solutions that are vertically aligned to their business – easy and fast to deploy.

DSA: In Malaysia who are the current users of business intelligence solutions? And will these same users implement Big Data?

Within our customer base, BI usage spans across verticals including banks, government, and retailers among others. While some have aspirations to implement big data in the future, the reality is that today, many are still learning to use Business Intelligence and Business Analytics tools. We believe that once they are familiar with the business benefits of BI and BA, we might start to see serious queries for big data. Before that they don’t want to do too many things.

DSA: How far are we from big data becoming mainstream in Malaysia? And which industries will likely steer the development of big data locally?

I would imagine at least 2 to 3 years away. Certainly the private sector will be keen to implement big data to cut operating costs. Within the government, big data will likely be used to gauge public sentiment analysis prior to implementing new policies.

DSA: Can you share some actual big data implementations Datamicron is currently involved in?

We have a lot of Proof of Concept implementations on Big Data. We are working on mining unstructured data derived from social media platforms, for example, using existing tools. Some of these POCs revolve around being able to predict outcomes.

DSA: What is your suggestion to businesses trying to get a grip on big data for their business?

Any organization consideration needs to understand what outcomes they want to achieve with big data. Avoid big bang approach towards implementation. Take measured small steps learning from small implementations and fine tuning as the organization learns from each small step.

CARVING A COMPETITIVE FUTURE WITH BUSINESS INTELLIGENCE AN INTERVIEW WITH JIMMY TING HENG TOON, CO-FOUNDER AND MANAGING DIRECTOR OF DATAMICRON

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Fusionex is a Malaysian success story and a key player in the big data scene in the region. DSA caught up with Fusionex Managing Director Ivan Teh to find out more about why and how Fusionex has managed to ride the big data wave so well.

Ivan and his team discovered the big data opportunity very early on. In fact before it became the buzzword it is today, they were already “doing big data”. Fusionex came into being back in around 2007. Ivan and his colleagues (who come with data warehousing background) saw a few things on the horizon. They felt that analytics and business intelligence needed to be made easier and more elegant.

They also had the foresight to see that ingesting data from a multitude of sources was going to become critical.

Ivan explained that at the time they were already seeing the explosion of data from social media and Internet of Things (IoT). They knew that analytics was needed to make sense of it all.

“Fusionex Giant was developed with this forethought in mind and from the beginning it was designed to be data source agnostic with connections to unstructured data sources from day one,” he proudly beamed.

Ivan explained that having the connections to frameworks like Hadoop was important but for Fusionex. Simplifying the whole process of connecting to different data sources was also key.

In line with making analytics easy and accessible he explained that embracing other emerging technologies, perhaps not obviously linked to analytics and BI was also important. Citing BYOD as an example he elaborated that mobility is now critical for all analytics players. Ivan and his team were ahead of the curve in understanding that in today’s business world powerful analytic tools need to be available any place and any time and on

numerous formats.

BYOD has driven analytics to new heights in this respect. Fusionex understand that most business people carry and access data from multiple devices including tablets, phones, laptops and desktops. Ivan explained how they designed Fusionex Giant to be device agnostic so that reports are delivered looking “beautiful and elegant” no matter where you might be and what device you may be using.

He cautions, however, that whilst BYOD elevates analytics consumption it is not without risks including that of increased security threats. He points out that aesthetics and platform support should not be implemented at the cost of compromised security.

There is no doubt that analytics reports need to be visually stunning particularly on mobile devices and there is a lot of talk with Big Data applications about Visualisation. DSA posed the question on whether Visualisation is just a gimmick.

Ivan offered a candid assessment of the situation. In his view Visualisation is not a gimmick; it is a key part of analytics. “In our media rich world, people expect and want to see business data presented looking “beautiful”. In addition good visualisation can summarise complex data in ways that make it much quicker to digest and understand,” he adds.

Ivan also stressed that great visualisation can mask underlying gaps in a product. Ultimately the fundamentals of an analytics product are the most important thing. To drive the point he notes that there is no point having great visualisation if the data you are analysing is dirty.”

Ivan is seeing the interest in data analytics growing significantly, as people from all lines of business including the CFO’s office, operations, and executive management to name a few are coming to realise that to stay ahead of the curve requires instant answers at their fingertips.

He sees some companies embracing this, but warns that there are real challenges. Within some organisation not everyone “gets it” and a mindset change is required to truly embrace how today’s analytics can transform decision-making. Beyond that Ivan also notes tangible challenges.

“If we use the ‘dirty data’ analogy, implementing Big Data analytics requires a lot of thought and planning otherwise the risk that it will not deliver the promise is real,” he cautioned.

He points out that companies like Fusionex have built invaluable man-years of experience in navigating the journey. Much of this experience is built into the technology they develop. As an example Fusionex Giant can clean dirty data using algorithms that glean from these years of experience.

Having the opportunity to speak briefly with Ivan we got a glimpse into why Fusionex has been able to excel in their field. Their foresight to predict the big data boom has been key. But just predicting the boom would not have been enough. More important, Ivan and his team had the vision to understand how to capitalise on it. They have pioneered to deliver products and technology that people need, perhaps before those same people even realised they needed it.

Ivan is keen to make sure that whether your requirement or your data is big or small, when it comes to business intelligence and analytics, people should not be reticent or intimidated. He believes that analytics truly is a journey to actionable insights. “Think of the journey as a quest to achieve more in less time and perhaps leave the office earlier each day having achieved more,” he noted.

His advice is to “start small, think big and scale fast”, and he believes Fusionex can help any company of any size with that.

FUSIONEX THE ANALYTICS JOURNEY START SMALL THINK BIG SCALE FAST WITH IVAN TEH MANAGING DIRECTOR AT FUSIONEX

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The Deloitte Touche Tohmatsu Limited report “Global Powers of Retailing 2014” paints a positive outlook for the global retail sector driven by improving positions in developed economies and a growing affluent middle-class in developing/emerging markets. It also notes that the industry as a whole is facing a period of unprecedented disruption and change. It cites the impact of mobile network access on customers, markets and businesses as one dramatic example. It calls into question how retailers can fully anticipate the ways in which business models and markets might be affected by a broad set of technologies interacting with social and economic trends to share the future of retail.

One key challenge presented by all these technologies coming together in retail is the overwhelming amount of unstructured data to be managed and organized for use.

The South East Asian economies are projected to grow by 4 percent to 7 percent per annum over the 2012-2016 period. This is a significantly faster pace of growth than is expected in advanced economies. Rising consumer spending on the back of growing disposable income coupled with a healthy tourism industry bodes well for the retail sector.

Malaysian retailers face similar challenges as the rest of the world – what technologies will power sustainable growth. One man has been at the foreground of helping Malaysian small and medium-sized retailers take on the challenge of harnessing technology to do just that.

Ooi Boon Sheng (OBS) is founder of Web Bytes Sdn Bhd. Data&Storage Asean (DSA) spoke to Ooi to understand the opportunities available to Malaysian

retailers around cloud computing and Big Data.

DSA: How did you get started with Web Bytes?

OBS: We started six years ago with four people to develop an online business solution. Around the time, there was no cloud computing; no software-as-a-service (SaaS). At the time we thought of developing software that would be available online and delivered via the Internet. But around the time, we also recognized that many retailers are not prepared for the cloud so we had to consider a hybrid model where part of the software resided on the client and other part delivered via the cloud. We needed to make sure that the combination was responsive and reliable. In a way, we made the cloud a practical solution for the retail industry.

Today, we are still a very small company with about 30 people half of whom are software engineers.

DSA: How did you decide which industry to focus on?

OBS: Early on we wanted to develop online software because it would allow us to scale. We studied the various industries and identified that nobody was offering online solutions in the retail sector. We noted that many of the IT solutions targeting retails were based on 1970 technologies. We saw our opportunity.

DSA: In the retail sector, price is a major factor for success. But knowing when to reduce prices is a challenge for everyone – big and small. How does Big Data solve this problem?

OBS: It really depends on the industry subsector. Within the apparel market, knowing when to reduce prices is not as important as understanding your

customers’ buying pattern. For example, we know that there is an increased in the number of people coming to shop from 8 to 10 in the evening during weekdays. We also understand that non casual buyers have objective for shopping. There is a lot of traffic from casual buyers; many come to malls to window stop and buy without objective. By understanding the why and when people buy, we are able to offer insight and strategy.

DSA: In an industry where margins can plunge in the face of competition, how can retailers afford expensive Big Data Analytics solutions?

OBS: It is true that business intelligence can be very expensive. Likewise some of the existing on-premise retail management solutions can also be steep. We took a different approach – subscription-based – to software acquisition allowing our customers to pay a monthly fee to gain access to analytical tools designed specifically for their market. What we discovered with this approach is that we are able to collect more data.

DSA: Where does one begin following a decision to implement Big Data?

OBS: I can’t speak for others but our approach begins with education. Our customers need to understand our approach/framework to big data and analytics. Sure, they can and should approach local retail industry associations to hear from their peers on how technology is reshaping the industry. Unfortunately these days, many of the members of these associations tend to focus on industry challenges and practices – very little around new technologies and how these are reshaping the industry.

HOW BIG DATA IS RESHAPING THE FUTURE OF RETAIL AN INTERVIEW WITH OOI BOON SHENG (OBS) IS FOUNDER OF WEB BYTES SDN BHD

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DSA: What are the issues retailers must always bear in mind when deploying Big Data?

OBS: A lot of retailers don’t know what big data can do for them. So when we discuss the technology, we share with them the relevancy of the information they can gain and big data can impact them.

DSA: Many predict the cloud to become the great equalizer as smaller companies can now afford technology comparable to those large systems deployed by big companies. Is that always the case?

OBS: The cloud does present an interesting opportunity for many companies. Once we explain to them that through the cloud, it is possible for smaller companies to now afford technology comparable to those used by big companies.

However I think small retailers need to be committed to invest in utilization. Today our hybrid solution is used by big chains as well as small shops. While cloud-based solutions may offer the same capabilities to all, what we noticed is that it is the large organizations that are actually benefiting from the platform because they are willing to invest not just dollars to pay for the usage of the technology but people who can be empowered and trained to use the technology. Smaller retailers simply don’t have the ability and know-how to use the technology (and unable to commit people to use it).

DSA: What conditions make it unrealistic to deploy a SaaS-based Big Data for a small company?

OBS: You are right, even SaaS is not for everyone. If a small retailer is not aiming to grow, it doesn’t make an impact deploying big data.

DSA: How does a retailer know when to give up on Big Data? Or even when Big Data is not the answer?

OBS: I think it is very difficult to answer that question at this stage.

DSA: Do you see Xilnex as a big data company?

OBS: Not yet but we are heading towards that direction. We are still learning. We are handling a lot of data today; analysing that huge data is a learning process. We are still improving as we understand more about the data.

DSA: Do you see big data opening new opportunities for you?

OBS: Yes. Put it another way, we make our difference because we are in the cloud.

DSA: How difficult is it developing a product in Malaysia? Are the skills readily available?

OBS: The good thing is that skill is readily available. Universities are churning out the skills we need. And because labour in Malaysia is cheap, it means that we compete with large MNCs that want the same people.

DSA: Do you sell outside of Malaysia and what are the different approaches to different counties and markets?

OBS: A unique differentiator for our solution is that it is designed from the ground up to be easy to deploy and use. We serve the same retail markets and because our solution is partly delivered via the cloud, we have customers in Singapore, Australia and Cambodia. Brands entering new emerging markets where local skills and infrastructure may not be up to par with international standards will find our offering as very cost effective.

HOW BIG DATA IS RESHAPING THE FUTURE OF RETAIL AN INTERVIEW WITH OOI BOON SHENG (OBS) IS FOUNDER OF WEB BYTES SDN BHD

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S i m p l i f y i n g G r o w t h

The challenge for any business, particularly retail in whatever shape or form i.e., brick and mortar, online or hybrid, is discovering what customers want, what price they are willing to pay for a product, and when they are most likely be willing to buy. According to the PricewaterhouseCooper report – https://www.pwc.com/es_CL/cl/publicaciones/assets/retailing2015.pdf – the value proposition that guides consumer product purchases is changing. Today consumers will put heightened emphasis on personalization. They are increasingly proactive in their purchase decisions and selective about with whom they want to do business.

This means that retailers can no longer depend on second guessing consumers. Technology is no longer just about improving operational efficiency; retailers need to understand and anticipate consumer needs. In this new paradigm, we are seeing a need to integrated real-time data that comes from a multitude of sources into demand management solutions. In this environment customer data and relationships will become a key asset for retailers.

Amazon and Nordtsrom are two examples of retailers that have successfully harnessed technology to enable them to anticipate what customers will likely buy based on their browsing behaviour online. They are also using data culled from social media to identify consumer interests; match these interests to products in their store; and are using technologies like recommendation engines to push new products to unsuspecting consumers.

But these organizations are not the typical Malaysian retailer. In fact whilst Malaysia

has its fair share or successful large retail businesses like 99 Speedmart, Econsave Cash & Carry, GCH Retail, Mydin, and Parkson, a sizeable number are actually SMEs. According to the http://www.acccim.org.my/file/2012%20SME_EN.pdf SMEs Survey, nearly 25 percent of 580,985 SMEs in the services sector are wholesalers and retailers. Many of these do not have the resources to invest in the kinds of technologies Amazon and Nordstrom are throwing at to solve the consumer puzzle – what the customer wants.

Seng Teong Chua, founder of Predictry, says this is the market that his organization wants to serve. Through cloud computing, he believes that Predictry can offer Malaysia’s SME retailers and wholesalers with the right technology to compete against the big boys. With funding from the Malaysian Development Corporation (MDEC), Predictry essentially provides relevant recommendations to shoppers through an in-house built algorithm that the company tweaks for each customer and site.

Chua explained his company today benefits from the success of Amazon. Many businesses that have used Amazon to reach customers recognize the value of a recommendation engine. Thus approaching these businesses to try Predictry’s solution is straightforward.

“Whilst Predictry is based in Malaysia, our customers are global. Our business, which is essentially a Recommendation-as-a-Service is hosted in the US and we serve customers all around the world,” he adds.

Chua says that retailers and marketers are fixated on conversion. But conversion is an on-going challenge for everyone. He reckons that conversion can best be

achieved through relevancy. “To provide relevant product recommendations, our recommendation engine tracks which pages shoppers go to. We are able to map out viewing and purchasing behaviour. We also use information mined from their connected social networks to gleam valuable insight about consumer behaviour,” he explained.

Chua says that Predictry is able to provide relevant recommendations to shoppers because the company tweaks its algorithm for each site. The company targets SMEs and ecommerce sites that do not have the resources to build their own recommendation engines.

Maturing cloud technologies, more localized systems designed for smaller retailers, will enable for a more level playing field even as retailing becomes more personal. In this future, customer data and relationships will become a key asset for retailers. In this future, the secret to sustained sales will be in knowing what the consumer wants even before they know it.

The AT Kearney 2014 Global Retail Development Index reports that Malaysia has a high income per capita and a vibrant young population (nearly half of Malaysians are younger than 25) making it a strong and stable market. The country’s online retail market is projected to reach US$3 billion by 2017. In that future market, access to affordable predictive technology may spell success for local retailers. Predictry is banking on this future.

SENSIBLY PREDICTING THE RETAIL BUSINESS OF TOMORROW WITH SENG TEONG CHUA, FOUNDER OF PREDICTRY

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Before Big Data became fashionable there was business intelligence and before business intelligence became an everyday phrase among business users, there was data warehouse. Therefore to truly understand Big Data and BI, one must go back to where it all began. Here’s a recap:

One of the benefits of relational databases was the ability to manipulate data to perform basic analysis and reporting. However, these required the assistance of IT to produce reports needed for analysis. Excel spreadsheets and Access databases replicated this capability for the everyday user. But both solutions did not offer the capability to perform ‘what if’ scenarios needed for predicting future outcomes. Data warehousing was created for this purpose but its complexity proved to be its biggest limitation as it required expertise beyond the business users meant to benefit from it. Business Intelligence systems were created to bridge the gap between the Excel and Access duopoly on the one hand and data warehouse solutions on the other. But even as user interfaces have been dumbed down to make it easier for you and me to begin to use the systems, ecommerce created the need to capture, store and manipulate large amounts of data and data types. Cloud computing and self-service accelerated this data explosion. Welcome to big data.

IDC expects the Big Data market in Malaysia to reach US$24.2 million in 2014 and sys that for big data to move into the next stage of maturity in the country (repeatable stage), organizations need to adopt a strategic approach to Big Data adoption as opposed to being siloed as is currently commonly seen. Liew Siew Choon, Market Analyst of Software Research at IDC Malaysia says “The Big Data market will grow bigger and enter into the next stage only when the issue of skillsets and resources are resolved. This in turn will lead to a complete ecosystem whereby channel partners with the right skills will have the capability to deliver end-to-end Big Data solutions, including

consultancy and other services.”

data&storageasean (DSA) spoke with Thomas How, managing director of Speedminer, on the state of business intelligence, business analytics, data warehousing and big data in Malaysia. 

DSA: Do you agree that there is a persistent misconception that BI and BA are the same and that data warehouse is just an extension of this?

THOMAS HOW: In my discussions with executives and IT professionals from different companies, it is interesting to observe that people have different understanding of what business intelligence, business analytics and data warehouse are. For us at Speedminer, data warehouse is a way to combine data from different sources into a single repository so you can perform some business intelligence and report on it. Business Analytics, for us, is about being able to perform predictive analysis. In a way BA is like data mining - you are trying to make sense of the data, potentially predict an outcome, and so be able to make better business decisions.

Today, people think that by having BI tools, businesses can perform predictive analysis. 

DSA: What is the problem with many of today’s data warehouse applications, including BI and BA? Where does big data sit in all this?

THOMAS HOW:  Most companies collect a lot of data about their operations. This could be from the production floor, from the warehouse, from sales and finance. Sure they can do very quick search, identify areas perhaps in the production process or billing or inventory. They are able to identify peaks and troughs in sales and factory outputs. But this is just one piece of the puzzle.

The reality is that a business relies on partners like suppliers who are outside the system. Customers are usually external to them as well. So to get a whole picture requires collecting data from outside and

mixing with the internal data to have a more balance picture of the business overall.

For example, if the Tourism Malaysia wants to understand what campaigns are well received among the thousands of visitors to the country, the might want to look at comments posted on its Facebook page or other popular community forums like Tripadvisor. They need to go to the internet, collect the data, and perhaps perform sentiment analysis, which they cannot do by relying solely on their own data.

It is possible that the enormity of the data and the variety of sources may mean that their current IT infrastructure cannot support the analysis. So they, again, may need to turn to an external party to help them undertake the analysis.

DSA: Comparing your customers in Malaysia versus those in more developed countries, where do you see are the differences in terms of (1) technology adoption; (2) business strategy; and (3) intent to use cutting-edge technologies to further the business?

THOMAS HOW: In Malaysia, only the government has the resources to make the necessary investments in data warehousing. Most private sector organizations sadly do not spend as much. And this may be partly due to old practices and beliefs that continue to this day. Let me explain. In many developed markets, companies recognize that to maximize the use of technology, you need to invest in professional services rather than just hardware and software.

In Malaysia, the prevailing practice is that companies are happy to invest in the tangible assets of hardware and software but not on the services. Sometimes during evaluations of IT solutions, there is lack of clarity on what is needed to get the best ROI. As such, many are unable to realize the full potential of their investments.

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DSA: Today, where is your core development team located? Do you find talent acquisition and retention an issue?

THOMAS HOW: Speedminer is a wholly owned Malaysian company. That said, we have nationals from China and India, for example, because finding local talent remains a big challenge for local ICT firms such as us.

As a MSC, we may have nationals from India and China but we are all based in Malaysia. Currently one of our bigger operational challenge is finding local talent so we bring in the skills we need from the region but the reality is that the number of people we want to hire is not enough.

DSA: As cloud computing take roots, are you seeing demand among customers shifting away from on premise to cloud base?

THOMAS HOW: The Malaysian government is probably the single biggest big data customer at this time. They have the resources, including a cloud datacenter in Putrajaya, to make start the big data revolution in Malaysia. Quite a lot of government departments are moving their servers to the datacenter.

Within the private sector, infrastructure cost is a key inhibitor towards building systems in-house. Cloud computing may be just what the private sector needs – unlimited infrastructure on a pay as you go model. 

DSA: In Malaysia, what needs to be done to accelerate adoption of big data solutions? Who should spearhead this adoption?

THOMAS HOW: I see customers in Malaysia that want to do analytics. The lack of in-house expertise is a problem. When we do analytics, it is not the normal BI people to do this. Sometimes they need statisticians to take full use of the

system especially in data mining. This expertise is what is lacking in the private sector. I believe that the impetus is on Government to spearhead the development on local experts to help accelerate adoption.

DSA: What should the Government do to accelerate adoption of big data in Malaysia?

THOMAS HOW: Local skills are clearly the missing ingredient. The Government could consider partnering with educational institutions to encourage students to take up the computing courses geared towards business intelligence and big data. I believe that when these graduates out to join the labor force, they will tell their employers the types of tools needed to get the job done.

DSA: Tell us a little bit about speedminer.

THOMAS HOW: We started in 1997 with about 10 people. Currently we have about 40-plus technical staff mainly around development. We originally focused on the healthcare industry; back in 1997 business intelligence and data warehouse were not common in Malaysia.

At the time the solutions were not mature; there were no significant products in the market. We saw the need and the opportunity; we were fortunate to have customers willing to explore the future with us. Armed with our experience and success in healthcare, we slowly move to other industries with solutions specific to the industry requirements.

From business intelligence, we have branched to Big Data. Many of our customers have huge amount of data. They recognize that information is valuable. Together with our customers, we are progressing towards big data. We are building a development platform in support of that strategic direction. We firmly believe in that future.

DSA: Any last thoughts to share with our readers?

THOMAS HOW: Today there is a disconnect between senior management (Board) and operations. Top management recognise the potential of the technology. Middle management and IT however see the operational challenges of in-house skills and processes that are not aligned to what the technology has to offer.

We believe that to truly reap the benefits of any technology, the organization needs to identify the problem, determine what they want to achieve, and from there to look for the solution and expertise to harness the potential.

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We are living in the age of the omni-channel retailing when retailers recognize that they need to connect their customers across multiple channels and touch points at the same time and even interchangeably. More and more retailers are giving customers the ability to connect, interact and complete transactions on their own terms. The end result is that a customer may view an item online, buy it using their mobile phone, and return it by dropping at the store. And they can do so in a smooth and seamless way.

Why are retailers doing this? Because customers today have choice and as such loyalty is at an all-time low. Industry studies reveal that annual churn in the wireless industry has risen from 17 percent 5 years ago to 32 percent last year. Banking customers increased the average number of financial institutions they frequent to 3.4 in 2000 up from 2.3 in 1996. Even in core retail categories like department stores, primary providers’ share of wallet declined more than 10 percent during a similar period.

A 2013 LivePerson study revealed that online shoppers will give brands no more than 76 seconds of their time if their needs aren’t met. Other studies suggest that the cost of keeping an existing customer is 10 percent of acquiring a new one.

And whilst retailers continue to invest in retention strategies including customer surveys, one company in Malaysia is recognizing that organizations must shift gears in order to better capture the customer experience/engagement process in real-time.

Data&StorageAsean (DSA) recently spoke to Kym Wong (KW), founder of Raydar Research, to understand where the engagement process is moving towards in the coming years.

DSA: How did you get started at Raydar Research?

KW: Back in 2005, we started Raydar Research we started providing online

research selling online panels for data to be collected. In 2010, we saw an opportunity to move the data collection process from online to mobile. At the time, mobile adoption was still very nascent and there were no tools available that track customer engagements via mobile phones. The proliferation of a wide variety of mobile devices and platforms complicated matters. And this is the challenge – to come up with a software that was device agnostic.

DSA: Who are your customers and what is the typical profile of a Raydar Research customer?

KW: From the beginning I knew that market research companies were not our target customers. At the time everyone was talking about mobile. We talked to companies like Nielsen and Milward Brown. But our key focus was companies that companies do customer service in-house. Banks have their own CRM systems. But these CRM systems come with basic survey modules. For example, how do you manage call down? We pitched to banks and we managed to get one of the largest retail groups in the world. The second group is healthcare. Because the core engine is a survey tool, we went to healthcare to convert their paper collection process into a mobile. For example, to audit hand hygiene, it used to be done manually. Today, we’ve converted this to a mobile device to help nurses collect as they move about their duties, with data collection done in the backend on the fly. This is now running in 20 hospitals in Malaysia.

DSA: What is the value proposition of Raydar Research?

KW: We have a core engine that can do quite a lot of things. Where we add value is increasing the customer’s productivity. For example, in the hospital data collection used to take months. Today with our technology, nurses are able to spend more time to tend to their patients even as we increase data integrity and accuracy. We focus on business outcomes. For the banks, we try to

understand the goals of the customer. We modify our system to track all relationship managers, for example, how they handle customer engagements in real time. This helps their managers better assess areas of improvement. We increase overall productivity by partnering with our customers and understanding what they really need.

DSA: As a business, how do you get heard above the noise?

KW: We are very industry focused. We don’t advertise. We go in to see the customer (for now, we focus on healthcare and banking sectors). The process is longer process, yes, but whatever is built after that is very long term – not likely to change quickly because the whole thing is custom-built.  We see many opportunities, especially in mobile, to help businesses to move some of their process more aligned to the changing dynamics of the customers.

DSA: There are high expectations about mobile data being able to generate a lot of intelligence about the customer. What is your view on this?

KW: Yes, a lot of data is being collected and, because of this, more intelligence about the customer particularly through their mobiles (of course provided we get their permission).  This allows us to understand consumer behaviour. When we start aggregating data on how people use their phone, we are able to gleam intelligence and find out what services are really meeting their needs. Big Data is the ability to predict behaviour but there are two sides to the coin: you need a data scientist with domain expertise; you also need to have a lot of data to give to the data scientist and perhaps psychologist. Without these you only have big data.

DSA: How do you ensure that partner / customer data is protected?

KW: In Malaysia, we comply with the Personal Data Protection Act 2010. Internally we have developed processes where data is on a need to know basis. We’ve put a lot of controls on our

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database, which today sits in the cloud. We monitor all the logs on a weekly basis for any irregular activities. This is all done in-house.

DSA: Do you think there is still a big untapped market for Raydar Research?

KW: Yes! We are still very focus on healthcare and banking. One bank we work used to conduct customer satisfaction surveys once or twice yearly. With the system we put for them, they can now do this customer survey every day. As a leader in global retail banking, this capability helps them monitor their reputation. We see the opportunity for other banks to do the same.

We are also going into property and manufacturing. A lot of training takes place in manufacturing. To track training, we’ve done Good Manufacturing Process (GMP) audits using our tools to effectively collect data and churn out reports instantaneously.

DSA: Do you see areas for improvement within your organization?

KW: The two key areas is user experience (generally) and user interface. We have a team of programmers but we don’t have people skilled in user interface. We need to re-work the flow to give excellent user experience. We are getting outside help for this. Next is business intelligence. We collect a lot of data for customers. There are other reports/data that we can generate that can help customers to make intelligence out of the data. We probably need to take in our own data scientist to help understand this data (to give value to our customers).

DSA: How do you achieve scale?

KW: Finding good programmers is a challenge. Our head of IT has been with us since the beginning. To achieve scale, we outsource part of the development process to different providers. We then bring everything together in-house. This

helps us achieve speed and scale. Our sales team also needs to be built in order to target new markets. We are not hiring door-to-door sales. We are moving to sell our services online and through social networks.

I think that infrastructure is the least of our concerns. Malaysian infrastructure is very good. The infrastructure at MSC is very good. With cloud, this is even better. We can build redundant systems.

People are our main concern. We look for people who are passionate about our customers. Our programmers go out to our customers to see how they create data. Where are the pain points? How do we improve the process? Our goal is to empower them to better understand their customers. 

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Wikipedia defines the Internet of Things or IoT refers to the interconnection of uniquely identifiable embedded computing-like devices within the existing Internet infrastructure. IoT is characterized expected to offer advanced connectivity of devices, systems, and services going beyond machine-to-machine communications (M2M) and covering a variety of protocols, domains, and applications. The interconnection of these embedded devices (including smart objects), is expected to usher in automation in nearly all fields, while also enabling advanced applications such as Smart Grid or the Smart Homes.

Early adoption of IoT are industry specific including heart monitoring implants in healthcare, biochip transponders on farm animals, automobiles with built-in sensors, or field operation devices that assist firefighters in search and rescue. Other examples include smart thermostat systems and washer/dryers that utilize WiFi for remote monitoring.

Arguably, one of the earliest implementations of IoT is in the use of sensing technologies like RFID, the initial usage of which are around inventory control and tracking, asset management, and monitoring job sites and work assignments to improve worker safety. RFID however, promises to do more as ecosystem technologies improve.

In Malaysia, one of the early proponents of RFID deployment and usage is MDT Innovations (MDTi), a majority owned subsidiary of Multimedia Display Technologies (MDT). MDTi’s core business includes component engineering, systems design, software development, and application solutions in: RFID; advanced display devices; and mobile information technologies.

The company’s core RFID activities are in research, design, development, implementation, and maintenance of RFID

key components and systems integration with customers in Japan, China, India, Indonesia, and Malaysia.

Data&StorageAsean recently spoke to MDTi’s general manager Sim Hon Wai to discuss the company’s role in the emerging IoT industry in Malaysia and Asia.

MDTi’s engineering competencies in RFID are attributed to its earlier involvement in design and development of advanced display products and RF components. Emphasizing on LCD-, PDP- (plasma), and OLED-based displays, the development of analog-digital boards, OSD (on-screen display) firmware, display drivers, video scalers, RF circuit design and HDMI modules had brought technology advancements to the company knowledge base not only in RFID products, but also in display products such as LCD & PDP televisions, LCD and CRT display monitors, DVB (-S,-T,-C) set top boxes, HDMI modules, mobile computing based displays and wireless AV (audio-video) transmissions.

DSA: Please tell us how you got started into RFID?

Sim: MDTi started out as a supplier of panel display monitors and LCDs. By 2002, we identified that the display monitor business was extremely competitive and unprofitable so we ventured into analogue digital conversion.

DSA: Which industries are at the forefront of RFID adoption?

Sim: Walmart is one of the first to popularize the use of RFID in retail and the supporting supply chain. From then on, the technology has been adopted by the largest retailers that saw the benefit of using RFID to tract inventory from warehouse to store floor. Other applications include freight tracking, warehouse management and track-and-trace.

DSA: How is the RFID adoption in Malaysia?

Sim: The Malaysian market is too small. For the moment, the Government is spearheading awareness and adoption. We have seen manufacturing adopting RFID as part of automation goals to enable systems to talk to each other with minimal human intervention. But again, the local market opportunity is small. For MDTi, 94 percent of our business is overseas with bulk of our business coming from India, China, Indonesia and Australia.

DSA: What and where do you see are the major hurdles for its continued/faster adoption?

Sim: It’s really about awareness and understanding of the potential of the technology to keep track of inventory, reduce wastage and lower cost. These are the early messages of the technology and its tied to the accepted benefits of tagging. However, we believe that longer term, the focus should shift on the business benefits of RFID including operational efficiencies and better intelligence through analytics.

DSA: Recently there have been talks about the connection between Big Data and Internet of Things. Please share your thoughts on this? How are they connected?

Sim: It really depends on the level of connectivity that the user wants. If the goal of adopting Internet of Things is to give the user tools to help in decision-making then yes, IoT will benefit with Big Data. Today, IoT is already with us thanks to the efficiencies that RFID brings to the operation. However, I personally think that Big Data is still several years into the future. Maybe by 2020, technology and business processes will have sufficiently matured to see the intersection of the two.

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DSA: MDT is primarily a RFID solution vendor. What is the role your company will play in the IoT story for Malaysia?

Sim: In the early 2000s we were known as pioneer in RFID. The term IoT has only begun to appear in technology vocabulary in the last two years. For our part, MDTi is rebranding ourselves as a IoT enabler through embedded innovation and development. The interconnect between RFID and IoT is very clear and because of this, you could say that MDTi is a pioneer of making IoT a reality for businesses and consumers.

DSA: Gartner predicts that by 2015, the focus will no longer be in the technologies that support or bring about IoT but in the applications themselves. What is your take on this?

Sim: I agree 100 percent. It is not for the sake of tagging things. It is about what you get after tagging these things. We see great potential beyond tagging and we plan to play in the market for a long time to come.

DSA: What is your advice to Malaysian businesses in the industry sectors you serve in terms of how they can ride this trend?

Sim: Users have to realize that eventually automation and analytics will be key to driving business forward. Malaysia is no longer cheap as labour is rising. Therefore Malaysian businesses have to look at ICT as a way to grow further forward. To adopt ICT they have to look at Big Data, perhaps IoT, to increase business efficiency, reduce labour cost and empower businesses with valuable insight.

DSA: What is role of government in this?

Sim: I think the Malaysian government is doing a great job to promote embedded technology to qualified research companies. It has identified IoT as the next wave and is actively working to position Malaysia to not only benefit from the technology as a user but to drive the development forward. Indeed the real challenge in Malaysia is for local market adoption. 

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With over forty years of experience in Information Science, specializing in large scale computing infrastructure and computationally intensive projects, Robert Hercus (RH) is arguably a man of interest. In 1977 he set up a software house specializing in application development for government agencies and private companies in areas such as finance, insurance, accounting and land registration systems, to name a few. He was also responsible for the implementation of the IT infrastructure and applications for Projek Lebuhraya Utara Selatan Sdn Bhd (PLUS) – owner and operator of toll expressways in Malaysia. He was further involved in setting up two pioneering Malaysian companies under PLUS for the development of automatic toll collection and the Touch ‘n Go systems.

In 2001, he founded Synamatix Sdn Bhd, which specializes in bioinformatics and a year later, Neuramatix Sdn Bhd, focusing on the creation of intelligent applications and devices in various domains including machine translation, robotic movement, robotic speech and semantic technology, among others. Robert is also the founder and Managing Director of Malaysian Genomics Resource Centre Berhad (MGRC), which specializes in genome sequencing and analysis, in addition to genetic screening. Founded in 2004, MGRC was listed on Malaysia’s ACE Market in 2010.

Data & Storage Asean (DSA) recently spoke to Mr Hercus on Big Data and how it impacts his work across several disciplines including life sciences, software development and personnel management

DSA: What is your definition of Big Data?

RH: Some would say that Big Data is data that is beyond the current computing systems’ ability to compute easily. Computers have been increasing in power every year so the focus on Big Data today is probably not just the petabytes of data

but the extraction and analysis of complex patterns as opposed to data processing per se. Much of the analysis today looks for information such as, the kind of products people buy, who relates to who, games people play, what do friends like in terms of music or video, etc. It is looking at relationships between people and objects or actions.

In the past, interest on data was centered on transactions, stock markets, accounting or payroll. The focus was on the data itself. Today, the interest revolves around the relationship between pieces of information

DSA: How does Big Data get applied to Neuramatix’s business?

RH: Our core technology NeuraBASE, is an ultra high-speed artificial intelligence technology that finds patterns within voluminous data sets and data streams. In general, we offer software and services to help analyse patterns and associations within voluminous data.

For genome analysis projects, NeuraBASE is used to detect and identify known and novel genetic mutations, which is important for understanding the development of diseases. In machine translation, NeuraBASE is used to build words and phrases from a source language, which are then linked to translated words and phrases of another language. We are also developing an interactive speech system, in which NeuraBASE is used to build sequences of phonemes, fundamental units of human speech that make words and phrases. To perform recognition, an algorithm is used to find a matching sequence of phonemes.

In each of these examples, we find application of Big Data, and there are other applications of Big Data. At any given moment, Bots are traversing the Internet looking for opportunities.

DSA: In Malaysia and specific to your business, are you involved in any Big Data projects?

RH:  We embarked on a collaborative effort with Sime Darby Technology Centre to analyse the gene expression data of oil palm a few years ago. The project involved the complete sequencing, assembly and annotation of the oil palm genome with 30 times coverage (repeated sequencing over 30 times) and with 93.8% completeness.

For machine translation, we have opened up a world of information to those who may not be fluent in English, specifically Malaysians and Indonesians. A human translator translates an average of 5-8 pages per day. In a world where an estimated 1.8 million articles published each year through an estimated 28,000 journals, there are much more information generated each day than human translators can cope. Much of this information changes rapidly. Our translation portal translates up to 200,000 words per minute. It takes seconds for us to translate entire websites. Our top users are mainly Malaysian public universities and corporate organisations. In 2013, we received 3.5 million visits from 104 cities worldwide. These include Malaysians who are either studying or working abroad.

One of our most interesting projects was a collaborative effort with the International Mesothelioma Program, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America. While this may not be strictly be a Big Data project which was initiated in Malaysia, we are proud to say that the bioinformatic analysis was completed here in Malaysia. In 2009, the paradigm for revealing the molecular cause of cancers relied on the interrogation of small numbers of genes, which limited the scope of investigation. The emerging second-generation massively parallel DNA sequencing technologies enabled more precise definition of the cancer genome on a large scale.

In this project, scientists from the International Mesothelioma Program, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America

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worked with us to examine the genome of a highly aggressive tumour associated with asbestos exposure. The project successfully uncovered thirty tumour-specific fusions/translocations which were independently validated. These discoveries help scientists understand how tumours develop and grow at the molecular level. Today, other scientists use genomic research to develop cancer drugs that can disrupt cellular signals for tumour growth. In some cases, tumours stop growing. In other cases, the size of the tumours were reduced. 

In addition to the above, we are also involved in robotics and the autonomous navigation of unmanned aerial vehicles.

DSA: Do companies need a data scientist in order to benefit from Big Data?

RH: If a company currently has an application that does what they want it to do, they probably don’t need a data scientist. However, if you are developing something new that has not been done before, you will definitely need a data scientist to work out the best ways to extract the relationships in your data. For example, if you look at Facebook and consider a person might have a hundred friends; and each of those friends have a hundred other friends; and that one person buys a particular item on Amazon. Is there a way for a business to identify from your friend’s friends who might be interested in buying the same thing? Is there a way to link up those potential customers? This kind of complexity requires a data scientist or computational algorithms to help extract insightful associations in real-time.

DSA: Is it easy to find a data scientist?

RH: It’s actually teamwork. You need a statistician trained in dealing with complex large data sets. You also need people who can translate that into computer jargon and program it. You then need system architects who can optimize the hardware for high performance.

DSA: Where do you see Big Data going in Malaysia?

RH: There is a lot of potential in the government sector for Big Data analysis, even simple things like processing car registrations licenses or petrol consumption subsidy management – are the right people getting the subsidies? Every country needs systems for tracking criminal activities, foreign workers, illegal immigrants and also smuggling activities – the UK government for example has done an excellent job at predicting the movements of criminal activities.

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Founded in 2007 Bumiputera MSC-status company eCEOs specialises in project management consulting and business intelligence, with presence in Indonesia, Mauritius, Iraq, Sudan, Australia, Italy and the Netherlands. Founder and CEO, Jailani Mustafa drew his inspiration for the company name eCEOs around the concept of virtualizing business process and project management. Over the years the company has developed a strong reputation within the oil and gas, telecommunications, government and the public sectors.

The company’s 120 employees come from eight nationalities and are grouped into three different departments: business development and strategic alliance, project management and software engineering. Change management is popular among organizations going through restructuring. He also observed a strong demand for change management in the region.

According to Mustafa business intelligence remains a growth market particularly in the public sector where managers and heads of departments are looking to make better cost-effective decision-making through technology and process innovation. At the same time, he feels a sense of disappointment that progress towards use of BI tools as a tool for solving complex business problems has remained slow.

DSA: What is hindering the wider adoption of business intelligence in Malaysia today?

Personally I feel that Malaysia is 10 years behind others in adopting these technologies and this is due to a general lack of appreciation and conviction at the leadership level; both in the government and private sector. The leaders are at these industries at these technologies as optional “technology toys” rather than as

mandatory tools to help them make better decision making. The word ‘solution’ is not generally equated to it because they just don’t see the true value of BI tools outside of report generation. 

DSA: In terms of adoption and usage locally, how has business intelligence change in three past five years?

We don’t see that much change. I would say that at this stage it hasn’t reached the level of sophistication I would expect. Senior management, in general, are still relying on excel-based reports – very traditional type of reports usually delivered to them by others within the organization. This lack of hands-on experience, for example initiating your own data queries, means you don’t develop direct appreciation for what BI can do outside of generating reports.

DSA: Are local businesses receptive towards BI tools?

I would say it’s ‘yes’ and ‘no’. Some customers have gone through various implementations of BI and there is a sense of scepticism in terms of the benefits of the technology. You have to understand that many are business executives of limited technology background. Some may have developed a high degree of expectations (perhaps brought about by media, analysts and vendors hyping technology) as to what BI tools can deliver particularly with access to real time data analysis. Many do not understand that for true real-time data analysis to be possible a lot of integration with various data sources needs to happen first. And unfortunately, this is not always the case.

This has resulted in a backlash of unmet expectations creating unnecessary resistance towards the further adoption of BI across a wider cross-section of businesses.

DSA: Business intelligence is predicted as a driver for Big Data adoption. Do you agree with this assessment, and why do you think this is so?

Yes. By definition big data is a natural extension of BI. What we have observed is that organizations that are successfully using BI tools generally desire to gain access to greater volumes of data, at high speed, various types of data as well as from different sources. At that stage they become receptive to consider new forms of processing information to enable better and faster decision-making, insight discovery and process optimization.

Are Big Data and Business Intelligence mutually exclusive?  According to some definitions (e.g., Gartner) yes.  But we consider them as the same technology domain.  In our company, Big Data is managed by our BI service line.

DSA: Malaysia remains behind in terms of business intelligence and big data adoption compared to its more mature neighbours. What needs to happen for this to change? Who should spear head it? 

Big Data needs to be appreciated beyond CIO fraternity. The CEO, the CFO, business and organizational leaders need to take ownership of Big Data initiatives.  They must say Big Data is “our baby”. 

DSA: What is eCEOs key differentiator when it comes to business intelligence? Likewise what is the company’s differentiator when it comes to big data? 

We see BI as a marriage of arts and science.  The science part is to how to extract and process data efficiently.  The arts part is how to give the WOW effect.  We believe we can put the two together better than our competitors.  We are new in Big Data, yes, but I am confident we will be good at it very soon.

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