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Big Data

Big data is a term for data sets that are so large or complex that traditional data processing application softwares are inadequate to deal with them. Challenges include capture, storage,analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. The term “big data” often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. “There is little doubt that the quantities of data now available are indeed large, but that’s not the most relevant characteristic of this new data ecosystem.”

Analysis of data sets can find new correlations to “spot business trends, prevent diseases, combat crime and so on.” Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, finance, urban informatics, and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research

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Processing

Storage of the Big Data

Hadoop

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Features of Hadoop: –

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MongoDB

When it comes for storage of BigData there is no better option than a NoSQL database and in particular to mention, MongoDB is one of the best.

Large-scale web organizations such as Facebook, Google and Amazon uses NoSQL databases to focus on narrowing their operational goals and employ relational databases as adjuncts where high-grade data consistency is necessary.

A NoSQL ( “non SQL” or “non relational” ) database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases.  NoSQL database design implements a key-value store, document store, column store or graph format for data.

Why MongoDB ?

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Software Development

Visualization of data

Technology Innovation, The Smart Choice !!

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