developing innovation through social collaboration: a case study in big data analytics

November 2011

Aster Data Developer Portal Overview: The First Community for Big Data Analytics

Co-presented with

Teradata Confidential and Proprietary33

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After the event, the

following materials will

be made available to all

of you:

• Presentation slides

• Webinar recording

• Chat transcript

Session Follow-up


Navdeep AlamMzinga Director of Data Architecture

@[email protected]

Steve WooledgeAster Data Center of Innovation,Teradata Corporation

Senior Director of [email protected]@Teradata.com

Introductions


Topic

Company & Case Study Overviews

Developer Community: Strategy & Results

Analytics: Measuring Business Trends

Q&A

5

Agenda


Market SaaS social software, services and analytics provider

Experience 40M users & 15,000 communities under management

Solution OmniSocial- social business ecosystem solution

# of Customers 300 clients

Sample Customers

Who is Mzinga?


Customer Experience

Employee Experience

PartnerExperience

Brand Experience

• Streamlined client acquisition

• Customer engagement

• Loyalty & retention

• On-demand support

• Listening & engagement

• Brand building

• Demand generation

• Social commerce

• Social business outsourcing

• Indirect revenue streams

• Developer networks

• Engagement & collaboration

• Satisfaction & retention

• On-boarding & recruiting

• Social learning

Mzinga Social Business

Ecosystem

Mzinga Social Business Ecosystem


Who is Teradata Aster?

The leading innovator in the ‘big data’ analytics market

Teradata Aster MapReduce Platform: MPP Analytic Platform with a MapReduce analytic framework within a database platform

For the Data Scientist: Brings the science of ‘big data’ to the masses with MapReduce functionality delivered through the analytic language of business, standard SQL

Delivers New Analytics: Provides businesses with new, breakthrough analytic applications with high-performance and pre-packaged pattern, path and graphSQL-MapReduce® analytic modules

On Multi-structured Data: Leverages multi-structured data sources for increased analytic breadth & accuracy

A Teradata product line as of April 2011Customers


What is “Big Data?”Big Data is more than size – it requires new technologies

“CIOs face significant challenges in addressing the issues surrounding big data…

New technologies and applications are emerging (examples include Hadoop and MapReduce)

and should be investigated to understand their potential value.”

Source: CEO Advisory: ‘Big Data’ Equals Big Opportunity, Gartner, 31 March 2011.

Relational

The Four Axes of Big Data


Other

Scientific (atronomy, genomes, physics)

Machine-generated (sensors, RFID, devices)

Spatial (long/lat coordinates, GPS output)

Web logs and clickstreams

Social media (blogs, tweets, social networks)

Unstructured (text, audio, video)

Events (messages, usually in real time)

Complex (hierarchical or legacy)

Semistructured (XML and similar)

Structured (tables, records)

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Examples of New Multi-Structured DataNew data types require more than SQL for rich exploration

†Source: “Big Data Analytics”, Survey of 325 companies. TDWI 2011

Data types collected as big data and/or using with advanced analytics

Diverse data types compound the big data analytics problem


Big Data Analytics:A Competitive Advantage Across Industries

Need for deep data analysis…on TB’s to PB’s of data…with minutes to seconds response times

Internet / Tech Use Cases

Financial Services & InsuranceUse Cases

Retail Use Cases

Media & Information

ServicesUse Cases

• Social networking graph analysis

• Crowd-sourcing

• Virality analysis

• Content targeting

• Advanced click-stream analysis

• Real-time fraud & link analysis

• Tick data analysis• Trading surveillance• Multi-variate pricing

analysis for insurance• Behavior pattern

matching

• Digital marketing attribution

• Online consumer behavior/patterns


• Online targeting for personalization/recommendations

• Predictive and granular forecasting


• Digital media consumer micro-targeting

• Ad optimization

“Analytics themselves don't constitute a strategy, but using them to optimize a distinctive business capability certainly constitutes a strategy.”

- T. Davenport & J. Harris, Competing on Analytics: The New Science of Winning


Analytic & Advanced Reporting Applications

Store

Process

Rapid Analytics Development

Embedded Analytic Processing

Massively Parallel Data Storage

• Commodity-hardware based• Software only, cloud, or appliance• Relational-data architecture can

be extended for non-relational types

• SQL-MapReduce® framework• Analyze both structured

& multi-structured data• Linear, incremental scalability

• 50+ pre-built analytic modules• Visual IDE; develop apps in hours• Many programming languages

Analysts Data ScientistsBusiness UsersCustomers

Develop

Teradata Aster MapReduce Platform


• New technology- Increase understanding of what can be done with:

• Teradata Aster MapReduce Platform

• Aster’s SQL-MapReduce® analytic framework

• Leverage knowledge of the group- Share custom code- Share ideas- Ask questions- Simplify development

• Provide peer support, reusable source code

• Grow community around Teradata Aster MapReduce Platformand SQL-MapReduce

Why Do Data Scientists Need a Community?

Accelerate use of SQL-MapReduce


Aster Data Developer Portal OverviewAccelerate understanding and adoption of SQL-MapReduce®

Aster Data Developer Portal

Currently available to all Aster Data customers and key partners

• Forums

• Code sample repository

• Expert blogs

• Collaboration features

Goal• Raise awareness of SQL-MapReduce

capabilities • Accelerate creation and adoption of

SQL-MapReduce analytic applications

Approach• Developer Portal for collaboration and

support of growing SQL-MapReduce user community

• Designed to facilitate sharing of SQL-MapReduce use cases and code

• Supported by Aster Data with code examples, expert content

• Initial launch to customers

Aster Data

Customers & Users


Best Practices to Foster Sharing and Information1 - Educate

• Become a one stop shopProduct documentation

Recorded marketing demos

Training decks

Blogs from thought leaders


Best Practices to Foster Sharing and Information2 - Engage

• Members need solid education foundation before communicating

• Then they are confident enough to begin engaging


Best Practices to Foster Sharing and Information3 - Incent

• Members have education, sense of community

Now show us what you’ve got


• Learn about SQL-MapReduce- Sources beyond Aster training

• Apply SQL-MapReduce technology to real-world problems

• Stand on the shoulders of others- New ideas and code for solving problems not yet considered

How the Community Benefits Data Scientists


• Internal Benefits- Increased value for customer

- Stronger knowledge base

• External Benefits- Thought leadership- Powerful branding

How the Community Benefits AsterCollaboration fosters learning, brand visibility, collaboration


ResultsGrowing knowledge base, satisfied customers

• Result: 90% of customers have registered• Engagement

- “Downloads” area is most visited area- “Discussions” is second most visited area

• Downloads area- This is a one-stop shop for Aster customers downloading analytic code- Analyze “Downloads” leverage content to grow “Discussions” area

• Up Next- Teradata Aster technical support leveraging portal for delivering

common SQL-MapReduce analytic modules- Roll out community to broader audience- Applying analytics more broadly to accelerate community engagement


Content, behaviors, activities & interactions

Business results

Social Intelligence & ROI


Mzinga Advanced Analytics Architecture

“Big Data” • Increased processing speed enabled by

proprietary algorithms

• Efficient loading, storing and analyzing of terabytes to petabytes of data

• Redundancy and failover support via advantages of MPP

Metadata: Blog Info, Profile Info, Relationship Info, etc.

Blogs, Comments, Discussions, Courses,

Programs, etc.

Audio & Visual

Text, Images,

etc.

Metadata Repository

Extensible Metadata Model

• Easily create your own reports and analytics by leveraging reusable data elements

• Increased development speed of your future analytics and reporting needs

• More flexible, comprehensive data insight, including comparative metrics

Flexible outputs• Multiple interactive dashboards, analytics

and report types, including shared and saved reporting to be available in stages

• Reduce report customizations


Analyze users & behaviors User activity, adoption & retention User engagement, influence, & trends User reputation & ranking

Use Cases Identify subject matter experts for

incentives based on activities and growth

Identify positive and negative trends that may impact your social strategy

Track content & apps Popular topics, rankings, & trends Popular applications

Sample metrics that matter


Analytics Platform

Visualizations

Consolidate and associate data from various sources

Analyze data for insights, trends, patterns and discover assets

Drive business decisions and connect with employees and/or customers

Intelligence Applications

Content Behaviors/Interactions Social GraphsVoices User Info Business Data

Recommendation BenchmarkingGamification Rewards ROI

Comprehensive business intelligence


Questions?


Thank you for joining us!

Stay engaged & learn more

• Participate in our Social Analytics Big Data surveyKeep an eye out for the invitation & chance to win!

• Visit asterdata.com to learn more about Big DataUpcoming events, best practices, and more!

• Visit mzinga.com to learn more about social analyticsUpcoming events, eBooks, and more!

developing innovation through social collaboration: a case study in big data analytics

Technology

science of big data

big data andor

big data analyticsnovember

big data new technologies

axes of big data challenges

multistructured data

rich exploration data

new analytics