Big data refers to the large data sets that can be studied to reveal patterns and trends to support business decisions. It’s called “big” data because organizations can now gather massive amounts of complex data using data collection tools and systems. Big data can be collected very quickly and stored in a variety of formats.
 The vast number of data collection avenues means that data can now come in larger quantities, be gathered much more quickly, and exist in a greater variety of formats than ever before. This new, larger, and more complex data is collectively called big data.
What makes big data “big”? 
Though there is no threshold that separates big data from traditional data, big data is generally considered to be “big” because it cannot be processed effectively and quickly enough by older data analysis tools.

Big data is broadly defined by the three Vs: Volume, Velocity, and Variety.
. Volume refers to the amount of data. Big data deals with high volumes of data.
. Velocity refers to the rate at which the data is received. Big data streams at a high velocity, often directly into memory rather than being stored on a disk.
. Variety refers to the wide range of data formats. Big data may be structured, semi-structured, or unstructured and can be presented as numbers, text, images, audio, and more.
What’s driving big data growth?
Emerging information technology has allowed data to be collected, stored, and analyzed at unprecedented scales. The internet continues to be adopted by new users in the US and across the globe, and developing technologies have allowed the internet to be integrated into many different products, creating numerous new sources of data. The millions of people watching Netflix, using Google, and buying products online daily contribute to the increasing volume and sophistication of big data.