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THE DATA LAKE DREAM Edd svds.com/StrataNY2014
2 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED.
3 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. A scalable, accessible repository of data (in its natural or processed state) WHAT IS A DATA LAKE?
4 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. CLEANVALIDATECONTROLPROTECT CONVENTIONAL DATA STRATEGY “WHAT YOU DO TO DATA”
5 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. MODERN DATA STRATEGY “WHAT YOU DO WITH DATA” TARGET VIP CUSTOMERS ATTRACT NEW CUSTOMERS AUTOMATE
6 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED.
7 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. TOWARDS THE “DATA LAKE” — Step 1
8 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. TOWARDS THE “DATA LAKE” — Step 2
9 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. TOWARDS THE “DATA LAKE” — Step 3
10 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. TOWARDS THE “DATA LAKE” — Step 4
11 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. UP vs. OUT — Enterprise Edition Different use cases put different demands on the data infrastructure. Increasing cost per unit of capability from scale- up architectures causes rationing of resources. Only the most valuable use cases are pursued. US Dollars Data Resource Usage Scale-up cost Scale-out cost UC1 UC2 UC3 UC4 UC5
12 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. THE DATA VALUE CHAIN DRAW VALUE FROM YOUR STRATEGIC DATA ASSETS Discover Ingest Process Persist Integrate Analyze Expose
1313 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. Make it cheap Failure as a feature Ask good questions Make it quick Both learning and adaptation Enable the feedback loop Don’t break things Make operations a platform for innovation APIs, platforms, simulation BUILD FOR EXPERIMENTS
14 © 2014 SILICON VALLEY DATA SCIENCE LLC. ALL RIGHTS RESERVED. THE EXPERIMENTAL ENTERPRISE We need to both support investigative work and build a solid layer for production. Data science allows us to observe our experiments and respond to the changing environment. The foundation of the experimental enterprise focuses on making infrastructure readily accessible.
15 Edd Dumbill Yes, we’re hiring! Want these slides? Go to: svds.com/StrataNY2014
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1 Results Based Monitoring (RBM) It is better to be approximately right than precisely wrong - John Maynard Keynes -
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McGraw-Hill/Irwin © 2004 The McGraw-Hill Companies, Inc., All Rights Reserved.
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® IBM Software Group © 2008 IBM Corporation Dr Tariq Aslam Business Alignment Using Enterprise Architecture Productivity, Governance, Innovation.
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