Big Data Big Data is the latest thing that we will see some companies to become best in class. There are of course skeptics who would oppose this statement that had been recently issued by a business journal but it actually makes a compelling case in today’s world filled with monstrous data that clearly consists of a lot of unstructured data gathered through the all penetrating social media. As much as it is hard to believe that 90{9d541b9d3b2964c9ff6bea9e8df948593b1de2f81106010f803b1d63dd962be0} of the existing data was created in the last two years, it is nothing less than true that 2.5 Exabytes of data that is being created every single day doubles every month.

Big Data is an umbrella term that is used to explain this availability, use and exponential growth of information. It is any kind of information that cannot be processed through a conventional database. Its three characteristics Variety, Volume and Velocity make it even harder for a conventional database deal with its exponential growth. For those of us interested to understand what do these characteristics mean here are three simple ways to explain.

Volume: This refers to the amount of information that’s able to be captured, tracked and stored. With data storage dropping, the amount of information companies are capturing will only continue to rise.

The key to dealing with volume starts with sifting through the data to determine what information is relevant, and assigning value to the relevant info.

Example:  FICO, or Falcon Credit Card Fraud Detection System, protects 2.5 billion active credit card accounts world-wide.

Variety: Data comes in many forms and only a small portion of it is numeric. That means there’s relevant data pouring in from multiple sources and much of it is difficult to quantify. Despite the challenge of identifying and measuring these sources, it still must be accounted for and considered in a company’s analysis and decision making process.

Example: In 2012, the White House announced the Big Data Research and Development Initiative, which explored how big data could be used to address important problems facing the government. The initiative was composed of 84 different big data programs spread across six departments.

Velocity: This not only refers to how fast the information is coming in, but how quickly it’s being processed in order to meet demand. Being nimble enough to react to data quickly is one of the major challenges most organizations struggle with.

Example:  Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes (2560 terabytes) of data. That’s the equivalent of 167 times the information contained in all the books in the US Library of Congress.