Big Data

Big Data has become a fashionable word in corporate world these days. However not every corporate executive who is using big data in his vocabulary vehemently knows what exactly its meaning is. The Big Data revolution has taken every company whether small or big by a storm. Every company is scrambling to do something about it without even having the exact idea of what it means.  Big data as its name suggests is a collection of data set which so huge in size that the conventional data analytics methods are incapable of processing any meaningful information out if it. Something as simple as average shopping bill of a million people can be called as the big data. Modern statistical and analytical tools have been developed which can find something meaningful out of such huge data sets.


To fully understand the big data, we need to take a step back and understand the context which has made big data so important for companies from all fields of economy. Modern payment methods such as credit card payment gateway and online payments have generated tremendous amounts of individual level data that can be used to predict consumer behaviour in future. Any such prediction has become very important for companies because then they can customize their marketing to focus on the needs of individuals.

Coming back to big data, retailing companies, banks, credit card companies, utility companies have all started using big data at multiple levels to predict consumer behaviour of their customers. However not all of them are fully sure about how to utilize the data that they are generating. Let us examine some of the application of big data analytics that these companies are using. Banks are using big data in a big way. Banks generate tremendous amount of data pertaining to financial behaviour of their customers. Banks know about each and every transaction that their customers make and hence for them big data analytics can prove to be great asset. By monitoring the financial behaviour of their customers, banks can very well predict that when a particular customer is going to default on his mortgage payment or a credit card. If a bank is able to predict defaults with fair accuracy then it can take corrective steps proactively. Similarly, credit card companies can also monitor the spending pattern of their customers and pin point those customers which are about to default.