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Big data analytics final

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  • 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
  • 7. THANK YOU

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