Big data

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Big data

  1. 1. Big DataINTRODUCTION:“Big Data” has become an extremely popular term, due to the well-documented explosion in theamount of data being stored and processed by today’s businesses. Big data is about more thanjust the “bigness” of the data. It may be defined as:“Big Data is too large amount of data to manage using typical database software tools.” 2012 - 2.7 Zettabyte (10^21) 2020 - 35 Zettabyte (10^21) Per day Twitter- 7 TB Facebook- 10 TBFACTORS: Volume Value BigData Velocity Variety
  2. 2. WHERE SEEN: Data warehouses OLTP(Online Transaction Processing) Social networks Scientific devicesFILTERING BIGDATA EFFECTIVELY: EXTRACT Raw feed of data TRANSFORM Usable set of data LOAD Usable data loading  Focus on important pieces of data.
  3. 3. WHY BIGDATA: Taking better decisions. Decide Acquire Organize Analyze (Distill) Product arrangement  Locating the dead zone. Generates financial values across sectors.RISKS: Will be so overwhelmed. Costing. Privacy.RISK MITIGATION: Need the right people & solve the right problems. It isn’t necessary to handle 100% data all the time. Formulate legal regulations.CONCLUSION:Banking industry was very hard to handle even a decade ago. But there are thousands of banksnow. So, the volume of “Big” will change but Big Data will continue to evolve.

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