Introduction to Data Stream Mining

Transcript

1. Introduction to Data Stream Mining
   Albert Bifet
   March 2012
   

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2. Motivation
   Source: IDC’s Digital Universe Study (EMC), June 2011
   Data is growing
   

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3. Motivation
   Memory unit Size Binary size
   kilobyte (kB/KB) 103 210
   megabyte (MB) 106 220
   gigabyte (GB) 109 230
   terabyte (TB) 1012 240
   petabyte (PB) 1015 250
   exabyte (EB) 1018 260
   zettabyte (ZB) 1021 270
   yottabyte (YB) 1024 280
   Data is growing
   

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4. Motivation
   Source: IDC’s Digital Universe Study (EMC), June 2011
   Data is growing
   

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5. Motivation
   Source: IDC’s Digital Universe Study (EMC), June 2011
   Data is growing
   

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6. Motivation
   Source: IDC’s Digital Universe Study (EMC), June 2011
   Data is growing
   

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7. Streaming Data
   Big Data & Real Time
   

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8. Big Data
   McKinsey Global Institute (MGI) Report on Big Data, 2011.
   Big data refers to datasets whose size is beyond
   the ability of typical database software tools to
   capture, store, manage, and analyze.
   

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9. Big Data
   McKinsey Global Institute (MGI) Report on Big Data, 2011.
   Big data refers to datasets whose size is beyond
   the ability of typical database software tools to
   capture, store, manage, and analyze.
   

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10. Methodology
    Sampling and distributed systems
    

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11. Methodology
    Paolo Boldi
    Big Data does not need big machines,
    it needs big intelligence
    

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12. Real time analytics
    We want to analyze what is happening now.
    

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13. Real time analytics
    We want to analyze what is happening now.
    

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14. Time and Memory
    Number 8 Wire Mentality
    Time and memory are the resource dimensions of
    the process.
    

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15. Time and Memory
    Time and memory are the resource dimensions of
    the process.
    

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16. Algorithms
    Classification, Regression, Clustering, Frequent
    Pattern Mining.
    

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17. Applications
    sensor data: industry, cities
    telecomm data
    social networks: twitter, facebook, yahoo
    marketing: sales business
    Data may come from: humans, sensors, or
    machines.
    

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18. Data Streams
    Big Data & Real Time
    

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