Big data refers to the recent trend of managing and processing increasingly large structured and unstructured datasets that are available to businesses. Big Data has been characterized by the alliteration of the “4 Vs of Big Data” – volume, velocity, variety and veracity (sometimes a fifth V is added for “value.” Big data is also arriving from different sources (vehicles, wearables, appliances, artificial intelligence), making it a challenge for traditional relational databases to handle with low latency.

Big data is important because of how it can be used and the vast and growing collection of new, exciting use cases that it has inspired. Through analysis, the data can show how to improve business inefficiencies, predict user and market behaviors, or to create new revenue streams and markets. Businesses can use big data to figure out why a product or service failed, detect fraud early and recalculate risks. More and more data is used in machine learning and artificial intelligence applications, which in turn will drive further data growth.

Examples of big data can include social media analysis, the stock exchange simulations, and to analyze complex systems and machines such as jet engines, oil derricks, and traffic systems. The application of big data is nearly limitless in scope and potential.

Related Articles:

• The essentials of a modern distributed database

• Reducing Costs and Cutting CO2 emissions – Aerospike Explores the Vital Role of a Real-Time Data Platform at Big Data & AI World

  Leading privacy-focussed global supply side platform Onetag to showcase how Aerospike has driven growth and role in the ad tech ecosystem

• Common mistakes designing a high-load database architecture