Taming the Beast: Extracting Value from Hadoop
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These slides - based on the webinar featuring Ingo Mierswa, CTO at RapidMiner, John Myers, managing research director at leading IT analyst firm Enterprise Management Associates (EMA), and Lyndsay Wise, research director at EMA - provide an overview of how to close the loop between predictive insights and action using big data analytics.
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Taming the Beast: Extracting Value from Hadoop
- 1. John L Myers Enterprise Management Associates Managing Research Director JMyers@EnterpriseManagement.com @johnlmyers44 Taming the Beast: Extracting Value from Hadoop Ingo Mierswa RapidMiner Founder & CTO imierswa@rapidminer.com
- 2. Panel Moderator Lyndsay Wise, Research Director, EMA Lyndsay has over 10 years experience in software research, BI consulting, and strategy development, specializing in software evaluation and best-fit solution selection. Her focus at EMA is on data integration, data governance, cloud technologies, data visualization, analytics, and collaboration. Slide 2 © 2015 Enterprise Management Associates, Inc.
- 3. Featured Speakers John Myers, Managing Research Director, EMA John has over 10 years of experience working in areas related to business analytics in professional services consulting and product development roles. Additionally, John helps organizations solve their business analytics problems, whether they relate to operational platforms – such as customer care or billing – or applied analytical applications – such as revenue assurance or fraud management. Ingo Mierswa, Founder & CTO, RapidMiner Ingo, an industry-veteran data scientist, is the founder and CTO of RapidMiner, the industry’s #1 open source platform for predictive analytics. Ingo is passionate about the technological innovation enabled by the open source community and envisions a world where easy-to-use predictive analytics software empowers all business analysts and data scientists. Ingo is the author of numerous award-winning publications about predictive analytics and big data, and has spoken at countless industry events. Slide 3 © 2015 Enterprise Management Associates, Inc.
- 4. A PDF of the PowerPoint presentation will be available Event Presentation Logistics for Today’s Webinar Slide 4 © 2015 Enterprise Management Associates, Inc. An archived version of the event recording will be available at www.enterprisemanagement.com • Log questions in the Q&A panel located on the lower right corner of your screen •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 Questions Event Recording
- 5. Join the Conversation… Submit your questions or comments to the panel using: @wiseanalytics @johnlmyers44 @rapidminer #predictiveanalytics Slide 5 © 2015 Enterprise Management Associates, Inc.
- 6. Topic #1: Issues With Data Lakes
- 7. Adoption of Hadoop-based Data Lake Architectures Slide 7 © 2015 Enterprise Management Associates, Inc.
- 8. Topic #2: Obstacles Implementing Analytics On Hadoop
- 9. Obstacles Implementing Analytics Slide 9 © 2015 Enterprise Management Associates, Inc.
- 10. Topic #3: Processing Requirements for Predictive Analytics
- 11. Required Processing and Compute Latency for Big Data Projects Slide 11 © 2015 Enterprise Management Associates, Inc.
- 12. ©2015 RapidMiner, Inc. All rights reserved. - 12 - Architecture of Hadoop Orchestration node Worker nodes
- 13. ©2015 RapidMiner, Inc. All rights reserved. - 13 - Leverage Hadoop’s Compute Capacity • Design advanced analytics workflows in your predictive analytics platform • Ensure your solution automatically translates predictive analytics needs into native Hadoop code, e.g., MapReduce, Hive, Pig, Spark, etc. • Push predictive analytic instructions into your Hadoop • Hadoop performs calculations across the entire Hadoop cluster for a holistic view of your data • Data remains in Hadoop Results are delivered to the business • Recommendations – GUI workflow language (code-free) – Don’t forget about security ResultsAnalytic instructions translated to native Hadoop Calculations Results operationalized in business processes Predictive Analytics Platform
- 14. Topic #4: Successful Big Data Analytics Projects
- 15. Project Success Slide 15 © 2015 Enterprise Management Associates, Inc.
- 16. ©2015 RapidMiner, Inc. All rights reserved. - 16 -
- 17. ©2015 RapidMiner, Inc. All rights reserved. - 17 - OPERATIONALIZE Predictive Decisions Close the Loop Between Insight and Action Embed predictive models into critical business processes Recommend best options for human or automated actions ©2015 RapidMiner, Inc. All rights reserved. - 17 -
- 18. Topic #5: Best Practices For Implementing Advanced/Modern Analytics
- 19. ©2015 RapidMiner, Inc. All rights reserved. - 19 - EFFORTLESS Predictive Analytics Immediately Empower Analysts to Anticipate Opportunity & Risk Easily Combine Any Data at Unlimited Scale with Any Model Code-Free, Lightning-Fast and Intuitive ©2015 RapidMiner, Inc. All rights reserved. - 19 -
- 20. Topic #6: Use Of Mixed Environments For Implementation Of Big Data Analytics
- 21. Growing Importance of Cloud Resources Slide 21 © 2015 Enterprise Management Associates, Inc.
- 22. ©2015 RapidMiner, Inc. All rights reserved. - 22 - - 22 - Design Once, Deploy ANYWHERE Leverage Investments in Existing and Future Systems Design predictive analytics independent of platforms Seamlessly execute predictive analytics in-memory or in any source, including data-at-rest or data-in-motion - 22 -©2015 RapidMiner, Inc. All rights reserved.
- 23. Topic #7: Evolving Role of the Data Consumer
- 24. What We Used to Think of Analytical Users Slide 24 © 2015 Enterprise Management Associates, Inc.
- 25. Empowering the Line of Business Slide 25 © 2015 Enterprise Management Associates, Inc.
- 26. Topic #8: Use Cases – Monetizing Insights Buried In Your Multi-Structured Data
- 27. ©2015 RapidMiner, Inc. All rights reserved. - 27 - Challenge Better understand TV viewing habits to prevent churn and optimize advertising “RapidMiner allows us to leverage Big Data, in real-time.” -- Avi Bernstein Professor at the University of Zurich, Department of Informatics Drive Broadcast Revenue and Customer Retention <5s time to generate high value activities based on predictive analytics Solution Process Big Data from three million TV viewers, in real-time, to make program recommendations and personalized advertising
- 28. ©2015 RapidMiner, Inc. All rights reserved. - 28 - Challenge Monitor corporate performance data in real time to identify correlations, outliers, and economic drivers “We benefit from the availability of community extensions via the RapidMiner Marketplace. We can easily search for what others have designed in RapidMiner, and use the extensions that are a fit for us.” -- Tom Gatten CEO Track Data from Millions of Companies to Identify Critical Economic Drivers 4.5 M subject matter experts’ content analyzed in the United Kingdom every single day Solution Use RapidMiner to mashup data of UK businesses, rapidly prototype predictive models & identify outlying, unusual, data
- 29. Where To Go From Here? Slide 29 © 2015 Enterprise Management Associates, Inc. • Data lakes are an emerging data management architecture • There are issues fully realizing value from data lakes • Following best practice/pattern helps
- 30. Join the Conversation… Submit your questions or comments to the panel using: @wiseanalytics @johnlmyers44 @rapidminer #predictiveanalytics Slide 30 © 2015 Enterprise Management Associates, Inc.
- 31. Q&A – Please Log Questions in the Q&A Panel Slide 31 © 2015 Enterprise Management Associates, Inc. • Visit RapidMiner.com to learn more about Effortless Predictive Analytics • Learn more about leading IT analyst firm Enterprise Management Associates (EMA) at enterprisemanagement.com