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The big question about big data

Big data is a term that describes the large volume of data that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important, its what organisations do with the data that matters. Big data can be analysed for insights that lead to better decisions and strategic business moves.

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Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before.

Although the concept of big data is new to many of us, the concept of large data sets go back to the 1960s and '70s when the world of data was just getting started, with the first data centres and the development of the relational database.

So, what is big data?

Big data is often characterized by the 3 V’s: the extreme volume of data, the variety of data types and the velocity at which the data must be processed.

Volume – Organisations and businesses collect data from a variety of sources, including online sales, client data and daily business transactions. In the past, storing all of this information would have been a problem, but new technologies have eased the burden.

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 - Data comes in all types of formats, from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions. Big data allows for all of this information to be suitable processed.

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 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 in near-real time.
  • Generating coupons at the point of sale based on the customer’s buying habits.
  • Recalculating entire risk portfolios in minutes.
  • Detecting fraudulent behaviour before it affects your organization.

Big data is used across a vast variety of sectors, from banking and healthcare to retail and manufacturing. Analysing big data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable. Data driven insights are often vital to the success of any business and organisation in order to make accurate investments or provide a service that can make a difference to the customer base.