Big Data

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Overview:

As the name itself implies that Big data is a large volume of data, including both structured and unstructured data which overwhelms business on a day-to- day basics. Often, big data is characterized by 3Vs such as

  • Extreme volume of data
  • Wide varieties of data types
  • Velocity at which the data must be processed

Though you can equate big data to any specific volume of data, it is used to describe terabytes, petabytes and even hexabytes of data captured over time. Today, we can see Big Data, which is being generated by everything such as from multiple sources at an alarming velocity, volume and variety around us at all times. Even systems, sensors and mobile devices will transmit Big Data. To extract meaningful value from big data, it requires optimal processing power, skills, and analytics capabilities. In most of the enterprises, the volume of data is too big or it moves too fast and exceeds current processing capacity.

Why do organizations need Big Data?

Big Data helps companies to improve and perform operations faster, takes intelligent decisions, etc. When this data is captured, formatted, manipulated, stored or analyzed, it helps companies to gain useful insight to increase revenues, gain or retain customers, and improve operations.

Big Data a Volume or a Technology

Though Big Data seem to refer the volume of data, it’s not always the same; as it may refer to the technology when used by vendors. This is because, it includes tools and processes that an organization requires handling the large amounts of data and storage facilities.

Big data is changing the way of people within organizations that work together and it even helps employees to take better decisions. It can be deepening customer engagement, preventing threats and fraud, optimizing operations, and capitalizing on new sources of revenue. However, the increase in demand for insights requires a fundamentally new approach to architecture, tools and practices.

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