technology driving growth. kotak investor conference

www.persistentsys.com © 2012 Persistent Systems Ltd

Feb

ruary

3, 2012

1

Technology Driving Growth

Anand Deshpande

February 3, 2012


Feb

ruary

3, 2012

2

Computers as we know

them are history!


The technologies that

drive the consumer

web are moving to the

enterprise.

Feb

ruary

3, 2012

3

s

m o b i l e

c

i

a

c l o u d

a

t

a p p s


Feb

ruary

3, 2012

4

How many

toothbrushes

are sold in the

world last year?


Feb

ruary

3, 2012

5

How many

toothbrushes

are sold in the

world last year?

Source 1: 1.2 Billion

Source 2: 3.2 Billion


Rethinking the user …

Feb

ruary

3, 2012

6


Mobile devices are getting main stream in

the Enterprise

Enterprises are opening up to

‘bring your own device’ culture

Tablet is becoming the ‘device of

choice’ for enterprises

iOS and Android are a ‘must

have’ to reach end customers.

Win7 … still in the wait and

watch mode.

Application Scenarios

Mobilized legacy

applications

New Enterprise Apps that leverage mobility

Building task specific

mobile apps

Tablets

Smartphones

Hardened

Handsets

Feb

ruary

3, 2012

7


Tablets are driving a change in the

Enterprise

Primary Device

With Tablets as the primary device,

HTML5 will be the default environment

Feb

ruary

3, 2012

8


Apps apps everywhere!

Feb

ruary

3, 2012

9


Proliferation and wide deployment of 4G

networks will lead to the Internet of things

10

“Soon, almost every device will have a wireless chip and it will be the driver for Machine 2 Machine communications. Certain verticals such as medical equipment will see the earliest impact of these M2M connections.”

Dan Hesse

Chief Executive

Officer

Sprint Telecom

Feb

ruary

3, 2012


Putting Kinect Technology to Work

Feb

ruary

3, 2012

11


To summarize

• Mobile devices are getting mainstream. The CIOs have to support them.

• Tablets are driving mobile deployment. HTML5 will be the de-facto UI

standard.

• Video is the new voice.

• Mobile computing will provide the network layer for sensors.

• Sensors will generate large amounts of data. Must find ways to deal

with large volumes of data.

Feb

ruary

3, 2012

12


Feb

ruary

3, 2012

13


Anand Deshpande

February 3, 2012


What do the users want to do when they go

on-line?

Feb

ruary

3, 2012

14

www.persistentsys.com © 2012 Persistent Systems Ltd 15

Feb

ruary

3, 2012


Facebook gets 2.7 billion clicks of its "like"

button every day

Feb

ruary

3, 2012

16


• Facebook is an advertising company. Of its total revenues of $3.7bn in

2011, 85% came from advertising. And that is down from 98% and 95%

in the previous two years.

• The company makes $1bn in pure profit.

• Facebook has a total of 845 million monthly users and 483 million daily

users.

• Of its monthly users, half have used Facebook on their mobile. (But

there are no ads on its mobile site, so it makes no money from them.)

• The majority of its money comes from the US, but the majority of the

users are outside the country.

Facebook IPO 2012

Feb

ruary

3, 2012

17


• Google going IPO made $1.67 billion, Facebook is projected to be at

$10 billion.

• Facebook’s IPO will be the biggest of any tech company in history, 6x

bigger than Google’s.

• Only 3 US companies have had $10+ billion IPO’s, AT&T, GM, and Visa–

• If Facebook raises $100 billion, Mark Zuckerberg will rake in $25 billion.

That’s equal to $50 from each of his daily users.

• Even though it’s 4th in daily visitors, Facebook is 1st in ad revenue –

• More than 1 in 10 people on Earth use Facebook

Facebook IPO

Feb

ruary

3, 2012

18


Feb

ruary

3, 2012

19

Social Networking

in the Enterprise


virtual “gifts” representing a “pat

on the back” encourages high

performance and fosters team

spirit

eMee: Employee Engagement Portal

Feb

ruary

3, 2012

20


the “den” creates a sense of belonging and provides an

outlet for hobby groups and shared interests

Feb

ruary

3, 2012

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To summarize

• Social networking caused major revolution in the Arab world.

• Consumer Social Networking has started driving commerce.

More compelling than search based advertisements.

• What we have learned from consumer social networking will move to

the enterprises.

Feb

ruary

3, 2012

22


Feb

ruary

3, 2012

23


Anand Deshpande

February 3, 2012


Cloud computing is the platform for next

generation of IT innovation.

Feb

ruary

3, 2012

24


Feb

ruary

3, 2012

25


What is driving the adoption of cloud

computing?

Economics.

Feb

ruary

3, 2012

26


What is driving the adoption of cloud

computing?

• Illusion of infinite resources

• No up-front cost

• Fine-grained billing (e.g. hourly)

• Utility Computing: Pay-as-you-go computing

promises substantially reduced cost.

Economics.

Feb

ruary

3, 2012

27


Unused resources

We are grossly over-provisioned

• Capacity includes:

• Computer Servers

• Storage

• Software Licenses

• Network bandwidth

• Energy

• Air Conditioning

• Rent

• Maintenance Costs

• Operator Staff

Static data center

Demand

Capacity

Time

Re

so

urc

es

Slide Credits: Berkeley RAD Lab Feb

ruary

3, 2012

28


Heavy penalty for under-provisioning:

Poor quality of service – lost customers.

Lost revenue

Lost users

Reso

urc

es

Demand

Capacity

Time (days) 1 2 3

Reso

urc

es

Demand

Capacity

Time (days) 1 2 3

Reso

urc

es

Demand

Capacity

Time (days) 1 2 3

Slide Credits: Berkeley RAD Lab

Feb

ruary

3, 2012

29


Ideally, want optimal provisioning of

capacity across all resources.

Static data center

Data center in the cloud

Demand

Capacity

Time

Reso

urc

es

Demand

Capacity

Time

Reso

urc

es

Slide Credits: Berkeley RAD Lab

Reso

urc

es

Demand

Capacity

Time (days) 1 2 3 Pay-per-use

business models Feb

ruary

3, 2012

30


By operating at scale, improving utilization,

simplifying operations, standardizing, increasing

reliability, reducing energy and cooling

• hardware costs can be reduced 33-70 percent

• maintenance costs can be reduced up to 50 percent

• support costs can be reduced by as much as 33 percent

• floor space/facility costs can be reduced 33-50 percent

http://www-935.ibm.com/services/us/its/html/green-datacenter-svcs-landing.html Feb

ruary

3, 2012

31

http://www-935.ibm.com/services/us/its/html/green-datacenter-svcs-landing.html










Advantages of Cloud Computing

Agility Cost Device and

Location

Independence

Scalability

Multi-tenancy Security Maintenance Metering

Feb

ruary

3, 2012

32


Challenges for Cloud Computing

Privacy Compliance Legal Open source

Open standards Security Availability and

performance

Sustainability

and siting

Feb

ruary

3, 2012

33


Cloud Computing: Why Now?

Business factors

• Minimal capital

expenditure

• Pay-as-you-go billing

model

Economies of Scale in

the Data Center

• Experience of operating

data centers efficiently

Technology factors

• Pervasive broadband

Internet

• Maturity in Virtualization

Technology

Clean Slate Approach

• Multi-tenancy

• Challenging the status-

quo

Business challenges will accelerate the adoption of cloud computing.

Feb

ruary

3, 2012

34


To summarize

• Enterprises will move to the cloud – this is inevitable.

• The speed of enterprises’ movement to the cloud will depend on the

peer group and will be driven by CEOs/CFOs comparing savings on the

balance sheets of their peers.

• This is not a technical decision.

• Unfortunately, the vendors and the eco-system to migrate to the cloud

are not entirely ready.

• The cost of migrating/running legacy systems is not accurately factored

in and will be a big impediment.

Feb

ruary

3, 2012

35


Feb

ruary

3, 2012

36


Anand Deshpande

February 3, 2012


Infrastructure is moving to the cloud … applications are next! Data will move with the applications.

Feb

ruary

3, 2012

37


Data on the cloud will

enable new data-centric

business models.

Feb

ruary

3, 2012

38


5 Exabytes of information was created

between the dawn of civilization

through 2003, but that much

information is now created every 2

days, and the pace is increasing

Eric Schmidt,

Google CEO,

at the Techonomy Conference,

August 4, 2010 (1 exabyte = 1018 bytes )

Feb

ruary

3, 2012

39


Enterprise’s data is

Feb

ruary

3, 2012

40

www.persistentsys.com © 2012 Persistent Systems Ltd www.persistentsys.com

BIG DATA:

Why this BUZZ di?

Feb

ruary

3, 2012

41


• Relational Databases have successfully created a $100 Billion dollar/year

industry. Relational databases manage 100s of TB of structured data in

the enterprise well.

• Beyond structured data, today’s enterprise must manage large, ever growing quantities of unstructured data and public data to derive

insights. This data is not being leveraged for decision making.

• Data management techniques created and perfected by Internet

Companies are ready for enterprise use.

• This confluence of distributed internet-based data management systems

with relational systems is making it possible to derive insights from large

volumes of diverse data sources in the enterprise.

Summary: Internet Technologies are

coming to the Enterprise

Feb

ruary

3, 2012

42


• Enterprises traditionally have two data stacks:

• Data Stack 1.0: Operational Data Store

• Data Stack 2.0: Enterprise Data Warehouse

• Despite the two data stacks, more than 70% of enterprise data is not

“accessible” for analytics and decision making.

• This is because large amount of enterprise data is:

• Unstructured – variety

• Large Quantities – volume

• Real-time – velocity

• Time to establish Data Stack 3.0

• Data Stack 3.0: Big Data Stack

Summary: Time to setup Data Stack 3.0

Feb

ruary

3, 2012

43


• Transaction processing capabilities ideally

suited for transaction-oriented operational

stores.

• Data types – numbers, text, etc.

• SQL as the Query language

• De-facto standard as the operational store

for ERP and mission critical systems.

• Interface through application programs

and query tools

Data Stack 1.0:

Relational Database Systems for

Operational Store

Feb

ruary

3, 2012

44


• Operational data stores store on-line

transactions

• Many writes, some reads.

• Large fact table, multiple dimension tables

• Schema has a specific pattern – star

schema

• Joins are also very standard and create

cubes

• Queries focus on aggregates.

• Users access data through tools such as

Cognos, Business Objects, Hyperion etc.

Data Stack 2.0: Enterprise Data Warehouse

for Decision Support

Feb

ruary

3, 2012

45

http://en.wikipedia.org/wiki/File:Star-schema-example.png


Data Stack 2.0:

Enterprise Data Warehouse Systems

Standard Enterprise Data Architecture

Data Warehouse

Engine

Optimized Loader Extraction

Cleansing

(ETL)

Analyze

Query

Metadata Repository

Relational

Databases

Legacy

Data

Purchased

Data

ERP

Systems

Relational Databases

Application Logic

Presentation Layer

Data Stack 1.0:

Operational Data Systems

Feb

ruary

3, 2012

46


One in two business executives believe that they do not have sufficient information across their organization to do their job

Source: IBM Institute for Business Value

Despite the two data stacks ..

Feb

ruary

3, 2012

47


This is because only a small

fraction of the

• data in enterprise and

• data from public data

sources

is managed by the

enterprise data stacks!

Feb

ruary

3, 2012

48


Beyond the Operational Systems, data

required for decision making is scattered

within and beyond the enterprise

ERP Systems

CRM Systems

Enterprise

Data Warehouse

Structured

Data Sources

Email Systems Collaboration/

Wiki Sites

Document Repositories

Project artifacts

Employee Surveys

Customer Call

Center Records

Unstructured

Data Sources

Cloud

Data Sources

Public

Data Sources

CRM Systems

Expense

Management

System

Organizational

Workflow

Sensor

Data

Vendor

Collaboration

Systems

Supply Chain

Systems

Weather forecasts

Demographic Data

Maps

Location and

Presence Data

Economic Data

Social Networking

Data

Twitter

Feeds

Feb

ruary

3, 2012

49


What comes first -- Structure or data?

Schema/

Structure Data

Traditional Database Architectures have traditionally taken the schema

first approach.

How do you even start putting structure to your unstructured data?

Feb

ruary

3, 2012

50


Time to create a

new data stack for

unstructured data.

Data Stack 3.0.

Feb

ruary

3, 2012

51


Time-out!

Internet companies

have already

addressed the same

problems.

Feb

ruary

3, 2012

52


• Every month, over half a billion different people check

their email, post photos, chat with their friends, and do a

myriad other things on Yahoo! sites.

• 250 million tweets every day on Twitter ! (100 million at the

beginning of the year)

• 400 million web searches on Google every day

• Over a billion updates on Facebook every month.

Internet Companies have to deal with large

volumes of unstructured real-time data.

Feb

ruary

3, 2012

53


• Hosted service

• Large cluster (1000s of nodes) of low-

cost commodity servers.

• Very large amounts of data -- Indexing

billions of documents, video, images etc..

• Batch updates.

• Fault tolerance.

• Hundreds of Million users,

• Billions of queries every day.

Their data loads and pricing requirements

do not fit traditional relational systems

Feb

ruary

3, 2012

54


• It is the platform that distinguishes them from everyone else.

• They required:

• high reliability across data centers

• scalability to thousands of network nodes

• huge read/write bandwidth requirements

• support for large blocks of data which are gigabytes in size.

• efficient distribution of operations across nodes to reduce bottlenecks

Relational databases were not suitable and would have been cost

prohibitive.

They built their own systems

Feb

ruary

3, 2012

55


New companies have

created business

models to support

and enhance this

software

Internet Companies have open-sourced the

source code they created for their own use.

Feb

ruary

3, 2012

56


Open Source Rules !

Feb

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3, 2012

57

Hadoop

Infrastructure


What about support !

Feb

ruary

3, 2012

58

www.persistentsys.com © 2012 Persistent Systems Ltd www.persistentsys.com

How does one go about the Big Data

Expedition?

Feb

ruary

3, 2012

59


Ingest new

data

Run Big Data

Algorithms

Generate

reports and

insight

How does one go on a Big Data Expedition

Feb

ruary

3, 2012

60

Incrementally, Iteratively

http://www.sxc.hu/browse.phtml?f=download&id=1205759


Data Stack 3.0 Architecture

Email

Server

OLAP

BI Tools

Log

Serve

rs

Unstru

cture

d

data

source

s

Persistent Bigdata Library (PEBL)

Recomm

endation

Engines

Clusteri

ng

Algorit

hms

Graph

Algorit

hms

Cra

wle

rs and

Extra

ctors

DS 1.0

System

Big Data Platform

Map

Reduce

(PIG/jaql)

Text

Analytics

(AQL)

Hive

SQL

Statistics - R/

Predictive

Analytics

Ingest Process Visualize Feb

ruary

3, 2012

61

DS 2.0

EDW ELT

Insights

Seque

nce

Algorit

hms

Stats

Algorit

hms

http://hadoop.apache.org/


With the data that is now available …

• What business problems can be solved in a more cost-effective way?

• What business problems can be solved with the data that we are

collecting but not leveraging?

• What questions are we afraid to ask because we believe it will be too

difficult to answer them or it would take too long to get the answer?

• What business questions are simply not being asked?

• How does this fit-in with the currently deployed infrastructure? What do

we need to do beyond what we have?

What use is Data Stack 3.0?

Feb

ruary

3, 2012

62


Search Quality

• Typical Search Engine

• Web crawling in MR

• Analysis of web pages in MR

• Index creation is MR

• Search Quality algorithms like TF*IDF, Page Rank are MR

• Vertical applications based on search – Vacation Home

Web Crawling Analysis of web pages Inverted Index

Search

Runtime

Feb

ruary

3, 2012

63


What are they doing with big data:

Search Assist

Feb

ruary

3, 2012

64


Risk Modeling

• Identifying risk exposure from each customer. E.g. – a survey found that

• 2.2K (out of 100K) customers using CC at beer bars missed payments once

in 4 months

• In contrast only 530 customers using CC to pay dentist bill missed payments

once in 4 months

• Essentially – the enterprises have to analyze and co-relate the data

coming from multiple sources

• Usually such data needs to be loaded once (say previous 5 years data)

• No pure algorithm to find such conclusions – its manual skill

• But, analysts need to query the data in different ways

• Providing mechanism for generating fast reports helps!

Feb

ruary

3, 2012

65


Sentiment Analysis/Customer Churn

Analysis

• Web2.0 – people tend to put lot of opinions on blogs, discussion forums

• Sentiment analysis – typical workflow

• The first 3 steps are perfect MR

Crawl typical

blogging

sites

Text mining Data

analytics DB load Reporting

Feb

ruary

3, 2012

66


Recommendation Engine

• “Customer who bought this item also bought….”

• “People you may know…”

• Enterprise collect data on users, past transactions, their interests

• They try to use this data for such recommendations

Feb

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3, 2012

67



Recommendation

Feb

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3, 2012

68



Targeted Ad

Feb

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3, 2012

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Feb

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3, 2012

70


Anand Deshpande

February 3, 2012


As applications move to the cloud they

will lose their tight hold on enterprise data.

Enterprise data will be available on the

cloud as a service independent

of the application.

Feb

ruary

3, 2012

71


Data is getting separated from Enterprise

Applications and is accessible on the cloud

through independent APIs.

Application

Data Data

App API

Traditional Application

Scenario

Application running in

the cloud Feb

ruary

3, 2012

72


Cloud Vendors will aggregate enterprise

data. And make it available through APIs.

Feb

ruary

3, 2012

73


The impact of aggregate data

http://data.mint.com/

Feb

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3, 2012

74

http://data.mint.com/


Concur: Aggregating Travel Data

Feb

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3, 2012

75


Feb

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3, 2012

76


Insights

Public

Data

Aggregate

Data

Enterprise

Data

As Enterprise Data

moves to the

cloud, it would be

easier to combine

enterprise data

with aggregate and

public data

sources.

Feb

ruary

3, 2012

77


Beyond the enterprise applications,

large number of apps will be available

on a pay-per-use basis in the App Store.

Feb

ruary

3, 2012

78


There will be a hierarchy of apps with

different price points; all available on a pay-

per-use business model.

Business Process

Specific Apps

Task/Device

Specific Apps

Traditional

Applications will

be commoditized

on the cloud.

Aggregate

Data

Enterprise

Data Public Data

Feb

ruary

3, 2012

79

http://www.google.co.in/imgres?imgurl=http://www.socialtimes.com/wordpressnew/wp-content/uploads/2010/01/ipad-icon.gif&imgrefurl=http://www.socialtimes.com/2010/04/why-im-returning-my-apple-ipad-appl/&usg=__o9tg9pEJ0dzps0qAc6354gcT00M=&h=273&w=200&sz=31&hl=en&start=1&sig2=1Rp0SAaaRhDHq6wsdKrZZQ&zoom=1&um=1&itbs=1&tbnid=pU7CxLCShSNTOM:&tbnh=113&tbnw=83&prev=/images?q=ipad+icon&um=1&hl=en&rlz=1I7ADFA_en&biw=1259&bih=593&tbs=isch:1&ei=2EyrTNGLBIGsvgPXz4X3Bg

http://www.google.co.in/imgres?imgurl=http://icons-search.com/img/icons-land/IconsLandVistaHardwareDevicesIconsDemo.zip/IconsLandVistaHardwareDevicesIconsDemo-PNG-256x256-Smartphone.png-256x256.png&imgrefurl=http://icons-search.com/icons/smartphone.aspx&usg=__OZSAXYeadAKjgmNIZD24qOCsDyM=&h=256&w=256&sz=65&hl=en&start=2&sig2=AQkz3tFw-zT6NvREhX3B1w&zoom=1&um=1&itbs=1&tbnid=xYqmhDpzm-bDmM:&tbnh=111&tbnw=111&prev=/images?q=smart+phone+icon&um=1&hl=en&rlz=1I7ADFA_en&biw=1259&bih=593&tbs=isch:1&ei=8kyrTJC-KYKevgOnm-3tBg

http://www.google.co.in/imgres?imgurl=http://aatc.metrotech.org/images/icons/icon_iphone.gif&imgrefurl=http://aatc.metrotech.org/courses/it-professional/iphonedevelopment/&usg=__AzJU5AEKDh7d7MjZf1-MjgLOlkQ=&h=495&w=300&sz=41&hl=en&start=1&sig2=LxGA4RjsNt1wA6dp3mVk6w&zoom=1&um=1&itbs=1&tbnid=AaWJZbhjD6s-CM:&tbnh=130&tbnw=79&prev=/images?q=iphone+image&um=1&hl=en&rlz=1I7ADFA_en&biw=1259&bih=593&tbs=isch:1&ei=EE2rTK_5C5G4vQP79PjkBg











Products/Apps will be consumed in

ready-to-eat bite-sized portions

Feb

ruary

3, 2012

80


From the

App Store

Low per

Unit Cost

Zero Loyalty

Pay per

Use

Snap-in

Snap-out

The New App World

Feb

ruary

3, 2012

81


To summarize

• As applications move to the cloud they are taking data to the cloud as

well.

• Data on the cloud is now accessible through APIs independent of the

application.

• Cloud operators are aggregating data.

• The ability to combine Enterprise data, Aggregate data and Public data

is very powerful.

• The world is moving to “the world of apps.” Apps will be business

process specific or task/display specific.

Feb

ruary

3, 2012

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Feb

ruary

3, 2012

83


Anand Deshpande

February 3, 2012

www.persistentsys.com © 2012 Persistent Systems Ltd 84

Innovation through Gandhian

Engineering Getting more for less for more

Feb

ruary

3, 2012


India:

the source

and

the market

for innovation

85

Feb

ruary

3, 2012


Feb

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3, 2012

86


Anand Deshpande

February 3, 2012

technology driving growth. kotak investor conference

Technology

consumer social

enterprise

public data

data stacks

big data

2012 persistent

enterprise

slide credits