Evolution of Big Data
Defining Big Data

“Data-driven decision making, popularized in the 1980s and 1990s, has evolved into a

vastly more sophisticated concept known as big data that relies on software approaches generally

referred to as analytics”(Picciano, 2012). Big data is one of the great new frontiers of IT. Data is

exploding so fast and the promise of deeper insights is so compelling that IT managers are highly

motivated to turn big data into an asset that can be managed and exploited for their organization.

In information technology-big data refers to the extremely large volume of data

that needs to be captured, stored, searched, shared, analyzed and visualized.

Big Data is not just about lots of data, it is actually a concept providing an opportunity to find

new insight into and organizations existing data as well guidelines to capture and analyze

future data. It makes any business more agile and robust so it can adapt and overcome business

challenges. It is an overall measurement of large complex data, specifically data that falls into

the “3V’s model”: high volume, high velocity, and high variety. For example, big data can be

applied to the wealth of information derived from social media or data obtained from the billions

of mobile phones in use daily. In a business sense, big data is a part of analytics that relies on

analytic application to confirm anticipated information and trends about consumer behaviors and

drive competition.

The 3V’S – Characteristics of Big Data

The 3Vs is a term used to define the different attributes of big data - volume, variety and

velocity. The 3Vs term was contrived to define the attributes that make up an organization's

stored and owned data warehouse. Today – the 3Vs term is used to define the trends and

dimensions of big