3. We‟d love your participation.
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
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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
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5. Agenda
Topic
Company & Case Study Overviews
Developer Community: Strategy & Results
Analytics: Measuring Business Trends
Q&A
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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
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7. Mzinga Social Business Ecosystem
• 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
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8. 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 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
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9. What is “Big Data?”
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.
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10. Examples of New Multi-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
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11. Big Data Analytics:
A Competitive 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
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12. Teradata Aster MapReduce Platform
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
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13. Why Do Data Scientists 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
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14. Aster Data Developer Portal 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
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15. Best Practices to Foster Sharing and Information
1 - Educate
• Become a one stop shop
Product documentation
Recorded marketing demos
Training decks
Blogs from thought leaders
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16. Best Practices to Foster Sharing and Information
2 - Engage
• Members need solid education foundation before communicating
• Then they are confident enough to begin engaging
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17. Best Practices to Foster Sharing and Information
3 - Incent
• Members have education, sense of community
Now show us what you‟ve got
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18. How the Community Benefits 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
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19. How the Community Benefits Aster
Collaboration fosters learning, brand visibility, collaboration
• Internal Benefits • External Benefits
- Increased value for customer - Thought leadership
- Powerful branding
- Stronger knowledge base
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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
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21. Social Intelligence & ROI
Content, behaviors, acti
vities & interactions
Business results
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22. Mzinga Advanced Analytics Architecture
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
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23. Sample metrics that matter
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
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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
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26. Thank you for joining 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!
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Notas del editor
We are delivering groundbreaking technology for analyzing new types of data quickly, at large volumes, for a growing set of customers.
(Audience may not be entirely technical, so worth explaining “big data”)
Updated with graphic from TDWI….
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.
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.
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.
* Built based on customer request for way to share their custom code with other customers trying to solve big data analytics challenges.
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
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.
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..
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.
Turn over to Nav to go through slide on Technology Community that he presented at PARTNERS
Turn over to Nav to go through slide on Technology Community that he presented at PARTNERS