Big Data - What is Big Data and Why it Matters!!


Big Data

The term “big data” refers to data that is so large, fast or so complex to handle it with traditional methods. The act of storing large amounts of data for analytics has been around a long time. But the concept of big data gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three V’s:

Volume: Organizations collect data from a variety of sources, including business transactions, IoT/smart devices, smart equipment, videos, social media and more. Storing this type of data would have been problem, but cheaper storage on platforms like data lakes and Hadoop have eased the burden.

Velocity: With the growth in the data streams and Internet of Things in to businesses at an unprecedented speed and must be handled in a timely manner. RFID tags, sensors and smart meters are driving the need to deal with these 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, emails, videos, audios, stock ticker data and financial transactions.

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 to enable

  1. cost reductions
  2. time reductions
  3. new product development and optimized offerings
  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.


















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