Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, and information privacy. In a 2001 research report and related lectures, META Group analyst Doug Laney defined data growth challenges and opportunities as being three-dimensional, i.e. increasing volume, velocity , and variety . Gartner, and now much of the industry, continue to use this "3Vs" model for describing big data. In 2012, Gartner updated its definition as follows: "Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization. Additionally, a new V "Veracity" is added by some organizations to describe it.
If Gartner’s definition (the 3Vs) is still widely used, the growing maturity of the concept fosters a more sound difference between big data and Business Intelligence, regarding data and their use:
· Business Intelligence uses descriptive statistics with data with high information density to measure things, detect trends etc....
· Big data uses inductive statistics and concepts from nonlinear system identification to infer laws (regressions, nonlinear relationships, and causal effects) from large sets of data with low information density to reveal relationships, dependencies and perform predictions of outcomes and behaviors.
A more recent, consensual definition states that "Big Data represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value".
To know more about this technology join hadoop trainings in hyderabad.Where you can get good knowledge on hadoop.
If Gartner’s definition (the 3Vs) is still widely used, the growing maturity of the concept fosters a more sound difference between big data and Business Intelligence, regarding data and their use:
· Business Intelligence uses descriptive statistics with data with high information density to measure things, detect trends etc....
· Big data uses inductive statistics and concepts from nonlinear system identification to infer laws (regressions, nonlinear relationships, and causal effects) from large sets of data with low information density to reveal relationships, dependencies and perform predictions of outcomes and behaviors.
A more recent, consensual definition states that "Big Data represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value".
To know more about this technology join hadoop trainings in hyderabad.Where you can get good knowledge on hadoop.
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