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Developing Innovation Through Social Collaboration: A Case Study in Big Data Analytics
This document provides an overview of the Aster Data Developer Portal and introduces the speakers. It discusses Mzinga's social business ecosystem solution and some of their customers. It then defines "big data" and how new data types require more than SQL for analysis. Examples are given of how big data analytics can provide a competitive advantage across industries such as financial services, retail, and media through use cases like fraud analysis, digital marketing, and predictive forecasting.
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Developing Innovation Through Social Collaboration: A Case Study in Big Data Analytics
- 2. Co-presented with Aster DataDeveloper Portal Overview: The First Community for Big Data Analytics November 2011
- 3. We‟d love yourparticipation. Being social is about interacting & engaging each Session Follow-up other & sharing ideas… so the best way to After the event, the experience it, is to just jump in and do it! following materials will be made available to all Feel free to tweet about our discussion (#mzinga or #asterdata) of you: • Presentation slides Join the chat. If you have any advance questions • Webinar recording during the presentation, just add them into the chat now and we’ll address them at the end of the • Chat transcript session We also know some of you will prefer to just listen; that’s cool too 3 Teradata Confidential and Proprietary
- 4. Introductions Steve Wooledge Aster Data Center of Innovation, Teradata Corporation Senior Director of Marketing @swooledge Steve.Wooledge@Teradata.com Navdeep Alam Mzinga Director of Data Architecture @yoshinav nav@mzinga.com 4 Teradata Confidential and Proprietary
- 5. Agenda Topic Company & Case Study Overviews Developer Community: Strategy & Results Analytics: Measuring Business Trends Q&A 5 Teradata Confidential and Proprietary 5
- 6. Who is Mzinga? 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 6 Teradata Confidential and Proprietary
- 7. Mzinga Social BusinessEcosystem • Social business outsourcing • Indirect revenue streams • Listening & • Developer engagement networks • Brand building Partner • Demand generation Experience • Social commerce Brand Mzinga Social Employee Experience Business Experience Ecosystem • Engagement & Customer collaboration Experience • Satisfaction & • Streamlined retention client acquisition • On-boarding & • Customer recruiting engagement • Social learning • Loyalty & retention • On-demand support 7 Teradata Confidential and Proprietary
- 8. Who is TeradataAster? 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 graph SQL-MapReduce® analytic modules On Multi-structured Data: Leverages multi-structured data sources for increased analytic breadth & accuracy A Teradata product line as of April 2011 Customers 8 Teradata Confidential and Proprietary
- 9. What is “BigData?” Big Data is more than size – it requires new technologies “CIOs face significant The Four Axes of Big Data challenges in addressing the issues surrounding big data… New technologies and applications are emerging (examples include Hadoop and MapReduce) Relational and should be investigated to understand their potential value.” Source: CEO Advisory: ‘Big Data’ Equals Big Opportunity, Gartner, 31 March 2011. 9 Teradata Confidential and Proprietary
- 10. Examples of NewMulti-Structured Data New data types require more than SQL for rich exploration Data types collected as big data and/or using with advanced analytics Structured (tables, records) Semistructured (XML and similar) Complex (hierarchical or legacy) Events (messages, usually in real time) Unstructured (text, audio, video) Social media (blogs, tweets, social networks) Diverse data types Web logs and clickstreams compound the big Spatial (long/lat coordinates, GPS output) data analytics Machine-generated (sensors, RFID, devices) problem Scientific (atronomy, genomes, physics) Other 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% †Source: “Big Data Analytics”, Survey of 325 companies. TDWI 2011 10 Teradata Confidential and Proprietary
- 11. Big Data Analytics: ACompetitive Advantage Across Industries Media & Financial Services & Internet / Tech Retail Information Insurance Use Cases Use Cases Services Use Cases Use Cases • Social networking • Real-time fraud • Digital marketing • Predictive and granular graph analysis & link analysis attribution forecasting • Crowd-sourcing • Tick data analysis • Online consumer • Advanced click-stream • Virality analysis • Trading surveillance behavior/patterns analysis • Content targeting • Multi-variate pricing • Advanced click-stream • Digital media analysis for insurance analysis consumer micro- • Advanced click-stream analysis • Behavior pattern • Online targeting for targeting matching personalization/ • Ad optimization recommendations Need for deep data analysis…on TB‟s to PB‟s of data… “Analytics themselves don't constitute a strategy, but using them to optimize a with minutes to seconds response times distinctive business capability certainly constitutes a strategy.” - T. Davenport & J. Harris, Competing on Analytics: The New Science of Winning 11 Teradata Confidential and Proprietary
- 12. Teradata Aster MapReducePlatform Analysts Customers Business Users Data Scientists Analytic & Advanced Reporting Applications • 50+ pre-built analytic modules Develop Rapid Analytics • Visual IDE; develop apps in hours Development • Many programming languages • SQL-MapReduce® framework Process Embedded Analytic • Analyze both structured Processing & multi-structured data • Linear, incremental scalability • Commodity-hardware based Store Massively Parallel Data • Software only, cloud, or appliance Storage • Relational-data architecture can be extended for non-relational types 12 Teradata Confidential and Proprietary
- 13. Why Do DataScientists Need a Community? • 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 Platform and SQL-MapReduce Accelerate use of SQL-MapReduce 13 Teradata Confidential and Proprietary
- 14. Aster Data DeveloperPortal Overview Accelerate understanding and adoption of SQL-MapReduce® Aster Customers Data & Users Goal • Raise awareness of SQL-MapReduce capabilities Aster Data • Accelerate creation and adoption of Developer Portal 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 • Forums • Expert blogs • Initial launch to customers • Code sample • Collaboration repository features Currently available to all Aster Data customers and key partners 14 Teradata Confidential and Proprietary
- 15. Best Practices toFoster Sharing and Information 1 - Educate • Become a one stop shop Product documentation Recorded marketing demos Training decks Blogs from thought leaders 15 Teradata Confidential and Proprietary
- 16. Best Practices toFoster Sharing and Information 2 - Engage • Members need solid education foundation before communicating • Then they are confident enough to begin engaging 16 Teradata Confidential and Proprietary
- 17. Best Practices toFoster Sharing and Information 3 - Incent • Members have education, sense of community Now show us what you‟ve got 17 Teradata Confidential and Proprietary
- 18. How the CommunityBenefits Data Scientists • 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 18 Teradata Confidential and Proprietary
- 19. How the CommunityBenefits Aster Collaboration fosters learning, brand visibility, collaboration • Internal Benefits • External Benefits - Increased value for customer - Thought leadership - Powerful branding - Stronger knowledge base 19 Teradata Confidential and Proprietary
- 20. Results Growing 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 20 Teradata Confidential and Proprietary
- 21. Social Intelligence &ROI Content, behaviors, acti vities & interactions Business results 21 Teradata Confidential and Proprietary
- 22. Mzinga Advanced AnalyticsArchitecture Metadata: Blog Info, Profile Info, Relationship Info, etc. Blogs, Comments, Discuss ions, Courses, Programs, etc. Audio & Visual Text, Images, etc. Metadata Repository “Big Data” • Increased processing speed enabled by proprietary algorithms Extensible Metadata Model Flexible outputs • Efficient loading, storing and analyzing • Multiple interactive dashboards, analytics of terabytes to petabytes of data • Easily create your own reports and analytics by leveraging reusable data elements and report types, including shared and saved reporting to be available in stages • Redundancy and failover support via • Increased development speed of your future analytics advantages of MPP and reporting needs • Reduce report customizations • More flexible, comprehensive data insight, including comparative metrics 22 Teradata Confidential and Proprietary
- 23. Sample metrics thatmatter Analyze users & behaviors User activity, adoption & retention User engagement, influence, & trends User reputation & ranking Track content & apps Popular topics, rankings, & trends Popular applications Use Cases Identify subject matter experts for incentives based on activities and growth Identify positive and negative trends that may impact your social strategy 23 Teradata Confidential and Proprietary
- 24. Comprehensive business intelligence Content Voices Behaviors/Interactions Social Graphs User Info Business Data Analytics Platform Visualizations Intelligence Applications Consolidate and associate Analyze data for Drive business decisions and data from various sources insights, trends, patterns connect with employees and/or and discover assets customers Recommendation Gamification Rewards Benchmarking ROI 24 Teradata Confidential and Proprietary
- 25. Questions? 25 Teradata Confidential and Proprietary
- 26. Thank you forjoining us! Stay engaged & learn more • Participate in our Social Analytics Big Data survey Keep an eye out for the invitation & chance to win! • Visit asterdata.com to learn more about Big Data Upcoming events, best practices, and more! • Visit mzinga.com to learn more about social analytics Upcoming events, eBooks, and more! 26 Teradata Confidential and Proprietary
Editor's Notes
- #9 We are delivering groundbreaking technology for analyzing new types of data quickly, at large volumes, for a growing set of customers.
- #10 (Audience may not be entirely technical, so worth explaining “big data”)
- #11 Updated with graphic from TDWI….
- #12 Although the “data scientists” performing big data analytics sounds like a very niche group, a variety of industries are confronting these challenges to gain a competitive edge. A lot of the technology was initially developed by Internet companies, but industries such as financial services, retail, and media are among those that are recognizing significant benefits. You can see some of the use cases they are tackling (INSERT EXAMPLES) in this slide.
- #13 Just as the “data scientist” is a new persona we see in the market, our SQL-MapReduce framework is a (relatively) new way to do advanced analytics. This graphic shows how the framework fits into Aster’s solution.
- #14 As I mentioned, data scientists are new personas, and SQL-MapReduce is a new tool. These analytics professionals may understand the use cases before they purchase Aster Data’s solution, but we need to continue educating current and potential SQL-MapReduce users about how our platform enables new and differentiated analytics. We can do provide this education through sharing and discussion of ideas and insightful examples.By building a community, we can improve the experience of data scientists using Aster Data’s products. We can increase information and resources available by facilitating collaboration and discussion and providing educational content.
- #15 * Built based on customer request for way to share their custom code with other customers trying to solve big data analytics challenges.
- #16 This is cutting edge techanology. We want to this community to be the one-stop shop for our customers to learn about it. We are provide everything we can:Product documentationDemos from marketingDetailed training slidesRecorded training webcastBlogs on cutting-edge ideas from Analytics teamAlso promote aggressively. Announcement builds on Analytics Center, Aster Data Developer Express initiatives announced earlier.Lead message per audience:Press: new community harnesses growing momentum around SQL-MapReduce as a critical tool for big data analytics, enabling collaborative development of solutions on Aster Data Analytic PlatformAnalysts: new community extends Aster Data initiative to provide comprehensive approach to enabling big data analytics, building on Aster Data Analytics Center and downloadable Integrated Development Environment. This initiative drives broader and faster adoption of Aster Data Analytic Platform and its competitive differentiators while accelerating innovation by expanding resources available to customersCustomers: new community offers exclusive access to expert discussion and sample code to valued Aster Data customer experts, enabling easier and faster creation of SQL-MR analyticsData scientists and other analytic developers: new community of experts enables rapid collaborative development of SQL-MapReduce analytics while enabling recognition of key experts
- #17 After users feel knowledgeable, they can ask intelligent questions. We can engage them with our support teams, analytics teams, field sales teams. Internally, we encourage anyone from within Teradata Aster who can answer questions or pose interesting topics to get involved. While we have a handful of people focused on developing content and posting it to the portal, it should not look like a one-man marketing show. We want thought leaders working directly with customers in here.
- #18 This is when your community becomes more self-sustaining. It will still require moderation and management – for example, you’ll need to monitor for questions directed to your organization, and send out regular updates on activity to keep users engaged – but your users have become the contributors, because you have provided the educational foundation for them to do soAnd MADE IT WORTH THEIR WHILEInitially, we hoped we could take the “if you build it, they will come approach,” despite some solid guidance from Mzinga. After all, we saw the obvious value in the community or we wouldn’t have built it in the first place. But in doing so we overlooked the fact that the very things that were driving us to create the community – the new technology, the opportunity to share information between customers, to grow the knowledge base – required us to follow this educational process.Key constraint is limited number of active SQL-MR users and limited SQL-MapReduce knowledgeWill grow as Aster Data customer base growsCan help accelerate growth with educational contentPeople need encouragement to come back to portalSend out occasional summaries of new, interesting information on portalCreate “learning paths” in portal that guide people to interesting and useful contentPeople needs incentives to share informationEnable badging system with rewards for badged usersRun contests and giveaways Add other ideas about how to engage – badge, gamification, etc..
- #20 While it is designed for Aster customers, the community also benefits Aster itself.Internally, we have achieved goals around customer value.Externally, we are recognized as a thought leader for launching the community.
- #26 Turn over to Nav to go through slide on Technology Community that he presented at PARTNERS
- #27 Turn over to Nav to go through slide on Technology Community that he presented at PARTNERS