Big data is a buzzword, an evolving term that describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information which is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity. Big data has the potential to help companies improve operations and make faster, more intelligent decisions. This data, when captured, formatted, manipulated, stored, and analyzed can help a company to gain useful insight to increase revenues, get or retain customers, and improve operations.
Big data describes an information management strategy that includes and integrates many new types of data and data management alongside traditional data. The concept gained momentum in the early 2000s when industry analyst “Doug Laney” articulated the now-mainstream definition of big data in the form of Vs:
- Volume – Volume indicates more data, it is the granular nature of the data that is unique. Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. Big data requires processing high volumes of low-density, unstructured Hadoop data. It is the task of big data to convert such Hadoop data into valuable information.
- Velocity – Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.
- Variety – New unstructured data types. Unstructured and semi-structured data types, such as text, audio, and video require additional processing to both derive meaning and the supporting metadata.
- Value– There are a range of quantitative and investigative techniques to derive value from data. Finding value also requires new discovery processes involving clever and insightful analysts, business users, and executives.
The term big data, especially when used by vendors, may refer to the technology which includes tools and processes that an organization requires handling the large amounts of data and storage facilities.
Importance of Big Data-
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:
- Determining root causes of failures, issues and defects
- Generating coupons at the point of sale
- Recalculating entire risk portfolios
- Detecting fraudulent behavior in the organization
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