The document outlines a webinar featuring experts discussing challenges and best practices related to Hadoop-based data lakes and predictive analytics. Key topics include issues with data lake adoption, implementation obstacles for analytics, and the importance of operationalizing predictive decisions. The discussion emphasizes the role of advanced analytics in driving business insights and the evolving landscape of data consumer roles.

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An archived version of the event recording will be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
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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
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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
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22. ©2015 RapidMiner, Inc. All rights reserved. - 22 -
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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
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25. Empowering the Line of Business
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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?
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• 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