Big Data

Big Data

 Big data refers to data that is so large, fast or complex that it’s difficult or impossible to process using traditional methods. 

The act of accessing and storing large amounts of information for analytics has been around for 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 transactions, smart (IoT) devices, industrial equipment, videos, images, audio, social media and more. In the past, storing all that data would have been too costly – but cheaper storage using data lakes, Hadoop and the cloud have eased the burden.

Velocity - 

       With the growth in the Internet of Things, data streams into 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

The importance of big data doesn’t simply revolve around how much data you have. 

The value lies in how you use it. By taking data from any source and analyzing it, you can find answers that

 1) streamline resource management

 2) improve operational efficiencies

 3) optimize product development

 4) drive new revenue and growth opportunities 

 5) enable smart decision making.