What is Big Data and Why is it Important?

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Big data is a popular term which describes the large volume of data – both unstructured and structured – that inundates a business on day-to-day basis. But it is not the amount of data that is important. It is what organisations do with data that matters. Big data can be analysed for insights which lead to strategic business moves and better decisions.

While the “big data” term is relatively new, the act of gathering and storing the large amounts of the information for eventual analysis is very old. The concept that gained momentum in early 2000s when the industry analyst Doug Laney articulated now-mainstream definition of the big data as three Vs:

Volume. Organisations collect the data from a variety of sources, which include business transactions, social media and information from machine-to-machine or sensor data. In past, storing it would have been a problem, but new technologies (like Hadoop) have eased this burden.

Velocity. The data streams in a great speed and must be dealt with in timely manner.

Variety. Data comes in all formats – from structured, numeric data in the traditional databases to the unstructured text documents, video, audio, email, stock ticker data.

Big data’s big potential

The amount of the data that is being created and stored on global level is almost inconceivable, and it keeps on growing. This means there is a greater potential to glean the key insights from business information,  yet only a tiny percentage of data is actually analysed.

Why Is Big Data Important?

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 analyse it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimised offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:

  • Generating coupons at the point of sale based on the customer’s buying habits.
  • Determining root causes of failures, issues and defects in near-real time.
  • Detecting fraudulent behaviour before it affects your organisation.
  • Recalculating entire risk portfolios in minutes.
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