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Are you ready for Big Data 2.0? EMA Analyst Research

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Enterprise Management Associates
Enterprise Management Associates

The document discusses new opportunities arising from Big Data 2.0. It provides biographies of the two presenters, Shawn Rogers and John Santaferraro, and outlines the agenda and logistics for the webinar. The presentation then covers the shift towards more sophisticated Big Data use, the emergence of hybrid data ecosystems combining traditional and modern data sources, and the technical drivers and common use cases behind Big Data projects.

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New Opportunities Arising: Are You Ready for Big Data 2.0? Shawn P. Rogers John Santaferraro VP of Research VP of Solutions/Product Marketing BI & Data Warehousing Actian EMA January 22, 2014
Today’s Presenters Shawn P. Rogers – VP of Research Shawn has more than 19 years of hands-on IT experience, with a focus on Internet-enabled technology. In 2004 he co-founded the BeyeNETWORK and held the position of Executive VP and Editorial Director. Shawn guided the company's international growth strategy and helped the BeyeNETWORK grow to 18 Web sites around the world, making it the largest and most read community covering the business intelligence, data warehousing, performance management and data integration space. John Santaferraro – VP of Solutions & Product Marketing With 20 years of experience in big data analytics and business intelligence, John has co-founded a data warehouse startup company and held executive business intelligence marketing positions in top tech companies like Tandem, Compaq, and HP. In addition, he founded his own consulting company, Ferraro Consulting, helping technology companies accelerate business by uniting sales and marketing around a common solution selling framework. Slide 2
Logistics for Today’s Webinar Questions • Log questions in the Q&A panel located on the lower right corner of your screen • Questions will be addressed during the Q&A session of the event Event recording • An archived version of the event recording will be available at www.enterprisemanagement.com Event presentation • A PDF of the PowerPoint presentation will be available Slide 3
New Opportunities Arising: Are You Ready for Big Data 2.0? Shawn P. Rogers Enterprise Management Associates Vice President Research – Business Intelligence, Data & Analytics SRogers@EMAusa.com January 22, 2014
The Big Data Shift • Big Data is changing faster than most technologies we seen in the BI/Analytic space. • A shift towards sophistication • Internet of things • Doing what was once impractical • Meeting New Enterprise Requirements • Speed of the Business • Diverse Data Slide 5 © 2014 Enterprise Management Associates, Inc.
Hybrid Data Ecosystem Slide 6 © 2014 Enterprise Management Associates, Inc.
Identifying Hybrid Data Ecosystem - Value • Structure – Data source organization, models versus late binding and additional uses. Schema Flexibility • Load – Mix of data types and sources adding value and challenge to environment, includes speed of data • Economics – The tipping point of ROI and investment • Analytics – Complexity of workload. Managing and overcoming obstacles of traditional systems • Response – Speed to scale. Speed to answer. Stretching the boundaries of traditional systems and infrastructure Slide 7 © 2014 Enterprise Management Associates, Inc.
The Sponsors of Big Data Slide 8 © 2014 Enterprise Management Associates, Inc.
Big Data Use Case by Year Slide 9 © 2014 Enterprise Management Associates, Inc.
Technical Drivers Slide 10 © 2014 Enterprise Management Associates, Inc.
Project Use Cases Slide 11 © 2014 Enterprise Management Associates, Inc.
Project Challenges Slide 12 © 2014 Enterprise Management Associates, Inc.
Data Sources for Big Data Projects Slide 13 © 2014 Enterprise Management Associates, Inc.
Hybrid Data Ecosystem Slide 14 © 2014 Enterprise Management Associates, Inc.
Who’s Using the Ecosystem? Slide 15 © 2014 Enterprise Management Associates, Inc.
HDE Platforms in Use for Big Data Slide 16 © 2014 Enterprise Management Associates, Inc.
Ways to Manage the Links between Nodes • Tools • ETL • Data Virtualization • Data Replication • Stack Approach Don’t create “cylinders of excellence” • Vendor lead and focused • Inside The Engine • Shared Metadata • Processing Options • Schema Binding Slide 17 © 2014 Enterprise Management Associates, Inc.
Summary • Sophistication – Process Driven Workloads, Real-time requirements • Highly integrated Ecosystems – Feature Rich, Agile and flexible. Orchestrated and smart • Higher levels of reuse, Skill gap reduction • Hybrid Solutions to meet Big Data 2.0 requirements Slide 18 © 2014 Enterprise Management Associates, Inc.
Actian Analytics Platform Accelerating Big Data 2.0 Confidential © 2014 Actian Corporation 19
88 Data Source & Type % Broader Than Data Scientists OF BIG DATA Transparency 15 $ New Possibilities TRILLION Universal Access % 1 Time To Value OF COMPANIES Confidential © 2014 Actian Corporation 20
Accelerating Big Data 2.0 - Winning Companies Do Big Data Analytics Predictive Real-time Insights & Events Unstructured Revenue EBITDA 8 9 Grocers 5 14 9 Online Retailers Big Box Retailers 9 5 1 11 Zettabytes 12 5 Casinos 2 9 10 -1 -15 Credit Cards 24 6 Insurance Analytics Enabled Processes -1 14 22 3 12 Big Data 11 Other Companies Cloud + Hadoop Surrounding Legacy Transformational Value Competitive Advantage – Risk Management – New Business Models Note: Percentage, 10 year CAGR McKinsey Report on Big Data. ** Actian estimate. Confidential © 2014 Actian Corporation 21
4 Big Achievements of Big Data 1.0 Enormous, Affordable Scale Massive Data Capture Data Discovery & Provisioning Emerging Data Everywhere Analytics are now the number one use case for big data! Confidential © 2014 Actian Corporation 22
4 Big Challenges of Big Data 1.0 Extreme Complexity Specialty Skillsets Enterprise-Class Capabilities Lagging Performance Big data challenges drive new technology requirements! Confidential © 2014 Actian Corporation 23
6 Building Blocks of Big Data 2.0 Cooperative processing delivers faster time6to value & better price performance Combining non-relational and relational data 4 enables a richer set of analytics Analytic building blocks provides accessibility for non1 skilled and lessskilled workers Unified platforms provide modular approaches covering 5 the entire analytic process Moving processing to the data operationalizes big 2 data and pushes toward real-time Services layers abstract away the complexity of 3 underlying infrastructure Confidential © 2014 Actian Corporation 24
Winning Companies Use Emerging Data to Create Transformative Value Digital data and the internet of things Everything has gone digital, trillions of time-stamped events are being created every day. Behavioral data and the proliferation of apps New wave of apps creates massive volumes of behavioral data tracking every move of users and driving hyper-segmentation. Conversational data and social media Social media has heightened awareness of the importance of conversations. Confidential © 2014 Actian Corporation 25
Winning Companies Use New Analytics to Create Even More Value Predict what is likely to happen Affinity, attribution, response rates, cost, revenue, economy, stock price, market movement Prevent something detrimental from happening Churn, risk, fraud, network failure, application failure, power outage, stock outs, attrition Prescribe the next best offer or action Ad optimization, upsell, cross-sell, upgrades, supply chain optimization, logistics, treatment Confidential © 2014 Actian Corporation 26
What We All Want – A Unified Platform VALUE DATA Customer Delight Competitive Advantage Risk Management New Business Models Enterprise Social Connect Analyze Act Internet of Things SaaS 1 Connect Connect anything with invisible integration across millions of data sources on-premise or in the cloud 2 Analyze Analyze everything with unconstrained analytics across entire ecosystems of data, users and applications 3 Act Automate action and events with real-time intelligence for anyone in the office or on the move Confidential © 2014 Actian Corporation 27
Actian Accelerates Big Data 2.0 Across the Entire Analytics Value Chain Value Data Enterprise Applications Data Warehouse Actian Analytics PlatformTM Connect Analyze Customer Delight Act Social Competitive Advantage Accelerators Internet of Things WWW Machine Data Mobile Accelerate Hadoop Accelerate Analytics Accelerate BI World-Class Risk Management SaaS Traditional NoSQL Disruptive New Business Models Confidential © 2014 Actian Corporation 28
Accelerate Everything ACCELERATE HADOOP ACCELERATE ANALYTICS & BI ACCELERATE ACTIONS 30-40X Performance Extreme Performance Low Latency Supercharged ETL Extreme Agility Complex Models Optimized Analytics Extreme Scale Mobile Enablement Confidential © 2014 Actian Corporation 29
Hadoop Analytics – Single Developer Actian Analytics For Hadoop = 25 Minutes Log Reader Filter Rows Group k-Means Avro Writer Coding MapReduce = 4 Weeks Log Reader Group k-Means MapReduce Code 30 Filter Rows MapReduce Code MapReduce Code MapReduce Code Avro Writer Avro Writer MapReduce Code Code MapReduce Confidential © 2014 Actian Corporation 30
Time to Analytic Value 85 Oracle Market Basket Analysis Connect Model Load Build Test Model Load Query :75 Actian Analytics Platform Connect Tune hours Build Test Tune Act for business value seconds Query Act for business value Confidential © 2014 Actian Corporation 31
Connect Anything Connect to any data or platform for greater precision 200 connectors, invisible connect, basic connect, advanced connect, on premise or cloud Prepare and enrich the data for increasing value Visual frameworks, libraries of functions, data flows, data provisioning, data quality Share computing and data for real-time accuracy On-demand integration, on-demand analytics, cooperative analytic processing Confidential © 2014 Actian Corporation 32
Analyze Everything Choose from hundreds of analytic building blocks Connections, transformations, analytics – ready for in-database or on Hadoop Rapidly assemble and reuse analytic workflows Visual framework, pre-built workflows, analytic blueprints, analytic solutions Deploy new analytic applications in days Accessibility for less-skilled workers, fast analytic iterations Confidential © 2014 Actian Corporation 33
Automate Action Optimize response to events with lower latency Processing complex models at higher speeds Increase the precision of automated decisions Emerging data, full data sets, increasingly sophisticated algorithms, Deliver real-time intelligence to anyone, anywhere Action Apps, visualizations, analytic services, embedded analytics Confidential © 2014 Actian Corporation 34
A Blueprint for High-Performance Big Data Analytics at Any Scale Extreme Performance – Extreme Scale – Extreme Agility Actian Analytics PlatformTM Hadoop Actian DataFlowTM Actian AnalyticsTM Data Warehouse Actian VectorTM Social Data Machines On Demand Analytics Machine Data Actian MatrixTM On Demand Integration Hadoop Enterprise Data Users Business Processes Actian DataConnectTM Applications SaaS Data Confidential © 2014 Actian Corporation 35
Questions and Answers Extreme Performance – Extreme Scale – Extreme Agility Actian Analytics PlatformTM Hadoop Actian DataFlowTM Actian AnalyticsTM Data Warehouse Actian VectorTM Social Data Machines On Demand Analytics Machine Data Actian MatrixTM On Demand Integration Hadoop Enterprise Data Users Business Processes Actian DataConnectTM Applications SaaS Data Confidential © 2014 Actian Corporation 36
For more information on Actian, visit: www.actian.com Slide 37 © 2014 Enterprise Management Associates, Inc.

More Related Content

Are you ready for Big Data 2.0? EMA Analyst Research

  • 1. New Opportunities Arising: Are You Ready for Big Data 2.0? Shawn P. Rogers John Santaferraro VP of Research VP of Solutions/Product Marketing BI & Data Warehousing Actian EMA January 22, 2014
  • 2. Today’s Presenters Shawn P. Rogers – VP of Research Shawn has more than 19 years of hands-on IT experience, with a focus on Internet-enabled technology. In 2004 he co-founded the BeyeNETWORK and held the position of Executive VP and Editorial Director. Shawn guided the company's international growth strategy and helped the BeyeNETWORK grow to 18 Web sites around the world, making it the largest and most read community covering the business intelligence, data warehousing, performance management and data integration space. John Santaferraro – VP of Solutions & Product Marketing With 20 years of experience in big data analytics and business intelligence, John has co-founded a data warehouse startup company and held executive business intelligence marketing positions in top tech companies like Tandem, Compaq, and HP. In addition, he founded his own consulting company, Ferraro Consulting, helping technology companies accelerate business by uniting sales and marketing around a common solution selling framework. Slide 2
  • 3. Logistics for Today’s Webinar Questions • Log questions in the Q&A panel located on the lower right corner of your screen • Questions will be addressed during the Q&A session of the event Event recording • An archived version of the event recording will be available at www.enterprisemanagement.com Event presentation • A PDF of the PowerPoint presentation will be available Slide 3
  • 4. New Opportunities Arising: Are You Ready for Big Data 2.0? Shawn P. Rogers Enterprise Management Associates Vice President Research – Business Intelligence, Data & Analytics SRogers@EMAusa.com January 22, 2014
  • 5. The Big Data Shift • Big Data is changing faster than most technologies we seen in the BI/Analytic space. • A shift towards sophistication • Internet of things • Doing what was once impractical • Meeting New Enterprise Requirements • Speed of the Business • Diverse Data Slide 5 © 2014 Enterprise Management Associates, Inc.
  • 6. Hybrid Data Ecosystem Slide 6 © 2014 Enterprise Management Associates, Inc.
  • 7. Identifying Hybrid Data Ecosystem - Value • Structure – Data source organization, models versus late binding and additional uses. Schema Flexibility • Load – Mix of data types and sources adding value and challenge to environment, includes speed of data • Economics – The tipping point of ROI and investment • Analytics – Complexity of workload. Managing and overcoming obstacles of traditional systems • Response – Speed to scale. Speed to answer. Stretching the boundaries of traditional systems and infrastructure Slide 7 © 2014 Enterprise Management Associates, Inc.
  • 8. The Sponsors of Big Data Slide 8 © 2014 Enterprise Management Associates, Inc.
  • 9. Big Data Use Case by Year Slide 9 © 2014 Enterprise Management Associates, Inc.
  • 10. Technical Drivers Slide 10 © 2014 Enterprise Management Associates, Inc.
  • 11. Project Use Cases Slide 11 © 2014 Enterprise Management Associates, Inc.
  • 12. Project Challenges Slide 12 © 2014 Enterprise Management Associates, Inc.
  • 13. Data Sources for Big Data Projects Slide 13 © 2014 Enterprise Management Associates, Inc.
  • 14. Hybrid Data Ecosystem Slide 14 © 2014 Enterprise Management Associates, Inc.
  • 15. Who’s Using the Ecosystem? Slide 15 © 2014 Enterprise Management Associates, Inc.
  • 16. HDE Platforms in Use for Big Data Slide 16 © 2014 Enterprise Management Associates, Inc.
  • 17. Ways to Manage the Links between Nodes • Tools • ETL • Data Virtualization • Data Replication • Stack Approach Don’t create “cylinders of excellence” • Vendor lead and focused • Inside The Engine • Shared Metadata • Processing Options • Schema Binding Slide 17 © 2014 Enterprise Management Associates, Inc.
  • 18. Summary • Sophistication – Process Driven Workloads, Real-time requirements • Highly integrated Ecosystems – Feature Rich, Agile and flexible. Orchestrated and smart • Higher levels of reuse, Skill gap reduction • Hybrid Solutions to meet Big Data 2.0 requirements Slide 18 © 2014 Enterprise Management Associates, Inc.
  • 19. Actian Analytics Platform Accelerating Big Data 2.0 Confidential © 2014 Actian Corporation 19
  • 20. 88 Data Source & Type % Broader Than Data Scientists OF BIG DATA Transparency 15 $ New Possibilities TRILLION Universal Access % 1 Time To Value OF COMPANIES Confidential © 2014 Actian Corporation 20
  • 21. Accelerating Big Data 2.0 - Winning Companies Do Big Data Analytics Predictive Real-time Insights & Events Unstructured Revenue EBITDA 8 9 Grocers 5 14 9 Online Retailers Big Box Retailers 9 5 1 11 Zettabytes 12 5 Casinos 2 9 10 -1 -15 Credit Cards 24 6 Insurance Analytics Enabled Processes -1 14 22 3 12 Big Data 11 Other Companies Cloud + Hadoop Surrounding Legacy Transformational Value Competitive Advantage – Risk Management – New Business Models Note: Percentage, 10 year CAGR McKinsey Report on Big Data. ** Actian estimate. Confidential © 2014 Actian Corporation 21
  • 22. 4 Big Achievements of Big Data 1.0 Enormous, Affordable Scale Massive Data Capture Data Discovery & Provisioning Emerging Data Everywhere Analytics are now the number one use case for big data! Confidential © 2014 Actian Corporation 22
  • 23. 4 Big Challenges of Big Data 1.0 Extreme Complexity Specialty Skillsets Enterprise-Class Capabilities Lagging Performance Big data challenges drive new technology requirements! Confidential © 2014 Actian Corporation 23
  • 24. 6 Building Blocks of Big Data 2.0 Cooperative processing delivers faster time6to value & better price performance Combining non-relational and relational data 4 enables a richer set of analytics Analytic building blocks provides accessibility for non1 skilled and lessskilled workers Unified platforms provide modular approaches covering 5 the entire analytic process Moving processing to the data operationalizes big 2 data and pushes toward real-time Services layers abstract away the complexity of 3 underlying infrastructure Confidential © 2014 Actian Corporation 24
  • 25. Winning Companies Use Emerging Data to Create Transformative Value Digital data and the internet of things Everything has gone digital, trillions of time-stamped events are being created every day. Behavioral data and the proliferation of apps New wave of apps creates massive volumes of behavioral data tracking every move of users and driving hyper-segmentation. Conversational data and social media Social media has heightened awareness of the importance of conversations. Confidential © 2014 Actian Corporation 25
  • 26. Winning Companies Use New Analytics to Create Even More Value Predict what is likely to happen Affinity, attribution, response rates, cost, revenue, economy, stock price, market movement Prevent something detrimental from happening Churn, risk, fraud, network failure, application failure, power outage, stock outs, attrition Prescribe the next best offer or action Ad optimization, upsell, cross-sell, upgrades, supply chain optimization, logistics, treatment Confidential © 2014 Actian Corporation 26
  • 27. What We All Want – A Unified Platform VALUE DATA Customer Delight Competitive Advantage Risk Management New Business Models Enterprise Social Connect Analyze Act Internet of Things SaaS 1 Connect Connect anything with invisible integration across millions of data sources on-premise or in the cloud 2 Analyze Analyze everything with unconstrained analytics across entire ecosystems of data, users and applications 3 Act Automate action and events with real-time intelligence for anyone in the office or on the move Confidential © 2014 Actian Corporation 27
  • 28. Actian Accelerates Big Data 2.0 Across the Entire Analytics Value Chain Value Data Enterprise Applications Data Warehouse Actian Analytics PlatformTM Connect Analyze Customer Delight Act Social Competitive Advantage Accelerators Internet of Things WWW Machine Data Mobile Accelerate Hadoop Accelerate Analytics Accelerate BI World-Class Risk Management SaaS Traditional NoSQL Disruptive New Business Models Confidential © 2014 Actian Corporation 28
  • 29. Accelerate Everything ACCELERATE HADOOP ACCELERATE ANALYTICS & BI ACCELERATE ACTIONS 30-40X Performance Extreme Performance Low Latency Supercharged ETL Extreme Agility Complex Models Optimized Analytics Extreme Scale Mobile Enablement Confidential © 2014 Actian Corporation 29
  • 30. Hadoop Analytics – Single Developer Actian Analytics For Hadoop = 25 Minutes Log Reader Filter Rows Group k-Means Avro Writer Coding MapReduce = 4 Weeks Log Reader Group k-Means MapReduce Code 30 Filter Rows MapReduce Code MapReduce Code MapReduce Code Avro Writer Avro Writer MapReduce Code Code MapReduce Confidential © 2014 Actian Corporation 30
  • 31. Time to Analytic Value 85 Oracle Market Basket Analysis Connect Model Load Build Test Model Load Query :75 Actian Analytics Platform Connect Tune hours Build Test Tune Act for business value seconds Query Act for business value Confidential © 2014 Actian Corporation 31
  • 32. Connect Anything Connect to any data or platform for greater precision 200 connectors, invisible connect, basic connect, advanced connect, on premise or cloud Prepare and enrich the data for increasing value Visual frameworks, libraries of functions, data flows, data provisioning, data quality Share computing and data for real-time accuracy On-demand integration, on-demand analytics, cooperative analytic processing Confidential © 2014 Actian Corporation 32
  • 33. Analyze Everything Choose from hundreds of analytic building blocks Connections, transformations, analytics – ready for in-database or on Hadoop Rapidly assemble and reuse analytic workflows Visual framework, pre-built workflows, analytic blueprints, analytic solutions Deploy new analytic applications in days Accessibility for less-skilled workers, fast analytic iterations Confidential © 2014 Actian Corporation 33
  • 34. Automate Action Optimize response to events with lower latency Processing complex models at higher speeds Increase the precision of automated decisions Emerging data, full data sets, increasingly sophisticated algorithms, Deliver real-time intelligence to anyone, anywhere Action Apps, visualizations, analytic services, embedded analytics Confidential © 2014 Actian Corporation 34
  • 35. A Blueprint for High-Performance Big Data Analytics at Any Scale Extreme Performance – Extreme Scale – Extreme Agility Actian Analytics PlatformTM Hadoop Actian DataFlowTM Actian AnalyticsTM Data Warehouse Actian VectorTM Social Data Machines On Demand Analytics Machine Data Actian MatrixTM On Demand Integration Hadoop Enterprise Data Users Business Processes Actian DataConnectTM Applications SaaS Data Confidential © 2014 Actian Corporation 35
  • 36. Questions and Answers Extreme Performance – Extreme Scale – Extreme Agility Actian Analytics PlatformTM Hadoop Actian DataFlowTM Actian AnalyticsTM Data Warehouse Actian VectorTM Social Data Machines On Demand Analytics Machine Data Actian MatrixTM On Demand Integration Hadoop Enterprise Data Users Business Processes Actian DataConnectTM Applications SaaS Data Confidential © 2014 Actian Corporation 36
  • 37. For more information on Actian, visit: www.actian.com Slide 37 © 2014 Enterprise Management Associates, Inc.