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Saturday, December 14, 2013

Scientific Computing: Big Data Analytics


What is Big Data?
Big Data is collections of set of large and complex data. It is not just about collecting them, it also about storing and warehousing this data. Warehousing the data include functions like capture, storage, search, sharing, transfer, analysis and visualization.

Traditional database system:
In the history we have come access various types of database systems like the navigational database system, relational database system, SQL database and NoSQL database systems. All these database system have a common problem which is the limitation in storage. In this digital world we are generating huge amount of digital data in our day-to-day life knowingly or unknowingly. Therefore the limitation is storage has risen as a critical problem.

Why Big Data Analytics?


Big data solves this problem by accommodating all the data we generate. Big data supports lots of data-types. Both structured and unstructured data can be processed and handled in Big data.

  • Discovery: As it stores various types of data, it is difficult to get a solution by querying it. Therefore we need some automated mechanism to search the data for us.
  • Iteration: With huge set of data, it hard to find where to explore the data to get out results. So iterative approach is used.
  • Mining and Predicting: Mining data and predicting results have become serious business. There are lots of start-up companies using this as the core idea. For example, The Climate Corporation is a San Francisco based start-up company which provides insurance to the farmers based on huge records of climate and weather data.
  • Decision Management: Concluding or deciding a thing from very huge set of data using traditional database is practically impossible. Therefore Big data plays key role in any decision making task. 

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