It’s Not About the “Big”             in Big Data
$26.5 BILLION  Nick Leeson      Jerome Kerviel      Kweku Adoboli      Bruno Iksil   Barings Bank     Societe Generale    ...
Hadoop in 2009
Hadoop 2012
Hype Cycle        We are         here
Crossing the Chasm        We are         here
Hadoop - Enabler
Database Harddrive                              Unstructured ( 61.7% growths )       time to find one record        =    lo...
Hadoop Harddrive      throughput                =   10MB/s      time to transfer record   =   10ms      10,000,000 * 10ms ...
Laws of Physics             Random             Sequential                                                             Valu...
People costHardware Cost
Time to insightTime for decision
Volume                        Data                        Size                      Data                    Complexity    ...
Impossible: 360 View
Game Changer     Slow         Static        Barrier                                 Business      ETL      Data Warehouse ...
NO - SQL                     RDBMS  Standard SQL   Structured Data     Response in sec.     No SQL      Unstructured Data ...
Common Applications               Asset Management Analytics                      Security Analytics                   Pro...
follow us: @datameer @stefanGroschupf
Not about the Big in Big Data
Not about the Big in Big Data
Not about the Big in Big Data
Not about the Big in Big Data
Not about the Big in Big Data
Not about the Big in Big Data
Not about the Big in Big Data
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Not about the Big in Big Data

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Not about the Big in Big Data

  1. 1. It’s Not About the “Big” in Big Data
  2. 2. $26.5 BILLION Nick Leeson Jerome Kerviel Kweku Adoboli Bruno Iksil Barings Bank Societe Generale UBS JPMC $1.4 billion $6 billion $1.4 billion $17.5 Billion Nasa $17.6BRogue Traders $26.5B
  3. 3. Hadoop in 2009
  4. 4. Hadoop 2012
  5. 5. Hype Cycle We are here
  6. 6. Crossing the Chasm We are here
  7. 7. Hadoop - Enabler
  8. 8. Database Harddrive Unstructured ( 61.7% growths ) time to find one record = logb N * 10ms log100(100,000,000) * 10ms = 40ms time to read record = 10ms 10,000,000 * 50ms = 5.8 days
  9. 9. Hadoop Harddrive throughput = 10MB/s time to transfer record = 10ms 10,000,000 * 10ms = 1.5 days random reads = (5.8 days)
  10. 10. Laws of Physics Random Sequential Values/Sec. 316 Disk 53,200,000 1,924 SSD 42,200,000 36,700,000Memory 358,200,000 1 10 100 1,000 10,000 100,000 1,000,000 10,000,000 100,000,000 1,000,000,000 Adam Jacobs The Pathologies of Big Data
  11. 11. People costHardware Cost
  12. 12. Time to insightTime for decision
  13. 13. Volume Data Size Data Complexity Sp ang es So ta Ch ee e urc Da do etyVe f ri loc Va y it
  14. 14. Impossible: 360 View
  15. 15. Game Changer Slow Static Barrier Business ETL Data Warehouse Intelligence Fast Dynamic View Raw Load Hadoop Data Pipeline
  16. 16. NO - SQL RDBMS Standard SQL Structured Data Response in sec. No SQL Unstructured Data Batch Hadoop
  17. 17. Common Applications Asset Management Analytics Security Analytics Product Cohort Analytics Advanced Web Analytics Structured + Many Unstructured Decision Makers Data Sources Data
  18. 18. follow us: @datameer @stefanGroschupf

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