© 2012 IBM Corporation Analytics Across the Enterprise Why Big Data and Analytics? Prepared by: Dennis Buttera – Curriculum Advisor 01 August 2014.

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© 2012 IBM Corporation Analytics Across the Enterprise Why Big Data and Analytics? Prepared by: Dennis Buttera – Curriculum Advisor 01 August 2014

2 Why Big Data and Analytics “The most competitive organizations are going to make sense of what they are observing fast enough to do something about it while they are still observing it.” Jeff Jonas, IBM Fellow and Chief Scientist, Context Computing, IBM Corporation “… analytics is no longer an emerging field; today’s businesses will thrive only if they master the application of analytics to all forms of data. Whether your office is a scientific lab, a manufacturing company, an emergency room, a government agency, or a professional sports stadium…” Brenda Dietrich, IBM Fellow and Vice President, Emerging Technologies, IBM Watson

3 What is Analytics? Mathematical or Scientific methods that highlight data for insight Insight = Competitive Advantage Used to inform actions and decisions Data is becoming the world’s new natural resource With analytics, insights are created to augment the gut feelings and intuition for decisions

4 Big Data and Analytics Demystified  Analytics is a progression of capabilities – start with the well-known methods of business intelligence – extend through more complex methods involving mathematical modeling and computation  Reporting is the most widely used analytic capability –gather data from multiple sources and create standard summarizations of the data –Visualizations are created to bring the data to life and make it easy to interpret.

5 Big Data and Analytics Overview

6

7 Descriptive Analytics – What Has Happened?

8 Predictive Analytics – What Will/Could Happen?

9 Prescriptive Analytics

10 Social Media Analytics

11 Entity Analytics

12 Cognitive Computing

13 Big Data

14 Big Data … just a little bit more!!!

15 Human brains were not built to process the amounts of data that are today being generated through social media, sensors, and more.

16  Relationships inferred from data today may not be present in data collected tomorrow  You don’t have to understand analytics technology to derive value from it  Fast, cheap processors and cheap storage make analysis on big data possible  Doing things fast is almost always better than doing things perfectly  Using analytics leads to better auditability and accountability. Emerging Themes

17

18 Analytics Across the Enterprise Paperback: 223 pages Publisher: IBM Press, 1 st Edition (28 May 2014 ) Language: English ISBN-10: ISBN-13:  This book demystifies the analytics journey by showing how IBM has successfully leveraged analytics across the enterprise, worldwide.  It provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business.