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Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
Why Business Intelligence is Broken...
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Why Business Intelligence is Broken...

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What do a hotel chain, a international soccer club and a toy company have in common? …

What do a hotel chain, a international soccer club and a toy company have in common?

They understand how to win with Business Analytics.

Check out Bruno Aziza's presentation for more details.

Bruno is VP Marketing at SiSense, a contributor at Forbes. He is an author and veteran in information management and has worked at Business Objects, Microsoft and Apple before SiSense.

Published in: Technology, Business
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  • After over 30 years, where, as experts in the field, we’ve prided ourselves with the idea that we knew EXACTLY the ONLY THINGS WE NEEDED TO MEASURE to make the right decisions, understand what was important, what wasn’t, we now have finally discovered the ONE thing that truly matters. Are you ready for that one thing?I’m going to give the one thing that you absolutely must measure all the time to make you are making the right decision…..…EVERYTHING
  • Transcript

    • 1. WHY BI IS BROKEN… ..WHAT YOU CAN DO ABOUT IT
    • 2. www.sisense.com
    • 3. http://future-bi.tv/
    • 4. DATA… …SCIENCE OR SERVICE?
    • 5. $17B BY 2015 ($3.2B in 2010)
    • 6. 1
    • 7. 8 Proprietary Data Enhancements Algorithms (PageRank for People)13 Social Networks Processed Every Day120 Terabytes of Data Storage200,000 Indexed Users Added Every Day100,000,000 Users Indexed Every Day1,000,000,000 Social Signals Processed Every Day10,000,000,000 API Calls Delivered Every Month54,000,000,000 Rows of Data In Klout Data Warehouse
    • 8. FERNANDO REDONDO 2 1. Transfers from Real to AC Milan for 15 million euros. 2. Injures his knee just 3 minutes into his first treadmill session. 3. Does NOT play for 2.5 years of his 3 year contract (16 games). 4. Retires.
    • 9. Predict with a 70% accuracywhether the player is going to get hurt or not.
    • 10. • Total practice days lost down 43%.• Use of medicines down 70%.• Player injuries dropped by 2/3.• Milan Lab allows Beckham to shed 40% of his body fat.
    • 11. 1980: 1TB of disk storage cost $14M2012: 1TB of disk storage cost $30M
    • 12. VS.
    • 13. VS.
    • 14. 52% OF COMPANIES HAVE NO ADBMS. TDWI World Conference, Chicago (June 2012)
    • 15. 3
    • 16. 12.14540 + 0.00117 winter rainfall + 0.0614 average growing season temperature – 0.00386 harvest rainfallPrinceton economist Orley Ashenfleter predicts Bordeaux wine quality (and hence eventual price) using a model. Ashenfelter was rightand Parker wrong about the ‘86 vintage, and the way-out-on-a-limb predictions Ashenfelter made about the sublime quality of the ‘89and ‘90 wines turned out to be spot on.
    • 17. To get Part 4 of Bruno’s presentation,Email inquiry@sisense.com

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