Big data analytics final

Big data analytics final

• 1.
  BIG DATA ANALYTICS Presented by : Samik Gupta Amit Kumar Siddharth Dixit Nishant Jain
• 2.
  WHAT IS “BIGDATA”?  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
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  WHEN TO CONSIDERBIG 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
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  WHAT CAN YOUDO 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
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  TECHNOLOGIES AND TOOLSUSED  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
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  BUSINESS BENEFITS  Detect, prevent and remediate financial fraud  Calculate risk on large portfolios  Execute high-value marketing campaigns  Improve delinquent collections
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  THANK YOU