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BIG DATA ANALYTICS


             Presented by :
                              Samik Gupta
                              Amit Kumar
                              Siddharth Dixit
                              Nishant Jain
WHAT IS “BIG DATA”?

   Big data is a term applied to data sets that grow so large and
    complex that it is beyond the ability of commonly used software
    tools to capture, manage, and process the data within a
    tolerable elapsed time.


   Characteristics of Big data:
       Volume
       Variety
       Velocity
       Value
WHEN TO CONSIDER BIG DATA SOLUTION?

   Big data solutions are ideal for analyzing not only raw
    structured data, but semi-structured and unstructured data
    from a wide variety of sources
   Big data solutions are ideal when all, or most, of the data
    needs to be analyzed versus a sample of the data; or a
    sampling of data isn’t nearly as effective as a larger set of
    data from which to derive analysis
   Big data solutions are ideal for iterative and exploratory
    analysis when business measures on data are not
    predetermined
WHAT CAN YOU DO WITH BIG DATA?

  •   Financial Services
       o   Fraud detection
       o   Risk management
       o   360- degree view of the customer
  •   Telecommunications
       o   Churn prediction
       o   CDR processing
       o   Network monitoring
  •   Retail
       o   360- degree view of the customer
       o   Click-stream analysis
       o   Real-time promotions
  •   Law enforcement
       o   Real-time multimodal surveillance
       o   Situational awareness
       o   Cyber security detection
TECHNOLOGIES AND TOOLS USED

   Technologies
    o   Massively parallel processing (MPP) databases
    o   Distributed file system
    o   In memory computing, etc.
   Tools
    o   Big Data by IBM
    o   Exadata by Oracle
BUSINESS BENEFITS

   Detect, prevent and remediate financial fraud

   Calculate risk on large portfolios

   Execute high-value marketing campaigns

   Improve delinquent collections
THANK YOU

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Big data analytics final

  • 1. BIG DATA ANALYTICS Presented by : Samik Gupta Amit Kumar Siddharth Dixit Nishant Jain
  • 2. WHAT IS “BIG DATA”?  Big data is a term applied to data sets that grow so large and complex that it is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time.  Characteristics of Big data:  Volume  Variety  Velocity  Value
  • 3. WHEN TO CONSIDER BIG DATA SOLUTION?  Big data solutions are ideal for analyzing not only raw structured data, but semi-structured and unstructured data from a wide variety of sources  Big data solutions are ideal when all, or most, of the data needs to be analyzed versus a sample of the data; or a sampling of data isn’t nearly as effective as a larger set of data from which to derive analysis  Big data solutions are ideal for iterative and exploratory analysis when business measures on data are not predetermined
  • 4. WHAT CAN YOU DO WITH BIG DATA? • Financial Services o Fraud detection o Risk management o 360- degree view of the customer • Telecommunications o Churn prediction o CDR processing o Network monitoring • Retail o 360- degree view of the customer o Click-stream analysis o Real-time promotions • Law enforcement o Real-time multimodal surveillance o Situational awareness o Cyber security detection
  • 5. TECHNOLOGIES AND TOOLS USED  Technologies o Massively parallel processing (MPP) databases o Distributed file system o In memory computing, etc.  Tools o Big Data by IBM o Exadata by Oracle
  • 6. BUSINESS BENEFITS  Detect, prevent and remediate financial fraud  Calculate risk on large portfolios  Execute high-value marketing campaigns  Improve delinquent collections