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A BIG DATA CHEAT SHEET: THE BIG PHARMA EDITION TAMARA DULL, DIRECTOR OF EMERGING TECHNOLOGIES C o p yrig ht © 2 0 1 2 , S A S I ns titute I nc . A ll rig hts re s e rve d .
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Big data PATIENT HOSPITAL FINANCIAL INSURANCE SCHEDULING 20% RECORDS ADMISSIONS DATA DATA DATA is not new. WORD EMAIL PDF FILES SPREAD- RFID TAGS SHEETS PROCESSING DOCUMENTS WEB LOG SATELLITE SOCIAL GPS DATA PHOTOS IMAGES MEDIA DATA 80% RESEARCH FORUMS LAB VIDEOS CLINICAL DATA RESULTS TRIALS MOBILE WEBSITE MARKETING AUDIO OPEN DATA DATA CONTENT DATA FILES C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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HERE’S OUR 3-4-5 PLAN: 3 Definitions 4 Trends 5 Questions C o p yrig ht © 2 0 1 2 , S A S I ns titute I nc . A ll rig hts re s e rve d .
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THE DEFINITIONS BIG DATA ―Big Data refers to electronic health data sets so large and complex that they are difficult (or impossible) to manage with traditional software and/or hardware; nor can they be easily managed with traditional or common data management ―That amount of data tools and methods… or complexity which puts you out of your Volume, Velocity, and Variety—often comfort zone.‖ referred to as the three V’s of Big Data— Paul Kent capture the true meaning of Big Data.‖ VP of Big Data SAS Institute SOURCE: Frost & Sullivan: “Drowning in Big Data? Reducing Information Technology Complexities and Costs for Healthcare Organizations” C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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THE DEFINITIONS HADOOP Is it a project… …or an ecosystem? NOTE: Hadoop is not synonymous with big data C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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THE DEFINITIONS DATA LAKE ―If you think of a datamart as a store of bottled water – cleansed and packaged ―A data lake is a storage repository that and structured for easy consumption – the holds a vast amount of raw data in its data lake is a large body of water in a native format, including structured, semi- more natural state. The contents of the structured, and unstructured data. The data lake stream in from a source to fill data structure and requirements are not the lake, and various users of the lake can defined until the data is needed.‖ come to examine, dive in, or take samples.‖ James Dixon CTO, Founder & Chief Geek Pentaho C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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The market is growing. SOURCE: http://wikibon.org/wiki/v/Big_Data_Vendor_Revenue_and_Market_Forecast_2013-2017 C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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The success rate is meh. C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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People issues trump technology issues. C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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Analytics keeps them coming back. C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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HERE’S THE 5 QUESTIONS: 1. What can Hadoop do that my data warehouse can’t? 2. We’re not doing “big” data, so why do we need Hadoop? 3. Is Hadoop enterprise-ready? 4. How is big data impacting Big Pharma today? 5. What are the primary threats to big data adoption? C o p yrig ht © 2 0 1 2 , S A S I ns titute I nc . A ll rig hts re s e rve d .
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QUESTION #1 WHAT CAN HADOOP DO THAT MY DATA WAREHOUSE CAN’T? $ 1. Store data more cheaply. 2. Process data more quickly (and cheaply). C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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QUESTION #2 WE’RE NOT DOING “BIG” DATA, SO WHY DO WE NEED HADOOP? Stage structured data. Process structured data. Archive any data. Process any data. Access any data. Access any data. (via data warehouse) (via Hadoop) C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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QUESTION #3 IS HADOOP REALLY ENTERPRISE-READY? For your organization: Maybe For all organizations: No Are we there yet? C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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QUESTION #4 HOW IS BIG DATA IMPACTING BIG PHARMA TODAY? C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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QUESTION #5 WHAT ARE THE PRIMARY THREATS TO BIG DATA ADOPTION? IT PRIVACY SECURITY analytics science business SKILLS C o p y r i g h t © 2 0 1 2 , S A S I n s t i t u t e I n c . A l l r i g h t s r e s e r v e d .
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