Big data is a large volume of data collected from various sources with an aim to analyze it and make better decisions based on the results of that analysis. The term Big Data is a relative term as it depends on the tools being used to handle the data and the capability of the analysts handling the data. For some organization gigabytes of data may be “big data” while others may use the term when referring to terabytes of data. Governments, scientists, drug manufacturers, meteorologists, finance executives, business administrators, advertising managers etc frequently have to manage Big Data.
Data can be structured as well as unstructured, and requires special software and large storage spaces for successful processing. In most cases, Big Data is a highly complex stream of data flowing in through servers at a rapid speed. Therefore, equipment used for handling it should be robust enough to deal with sporadic changes in reception of data.
The sources of Big Data are varied and so are the types of data they gather – it could be simple numbers like page views and conversions, text documents, videos, audios and images. However, Big Data becomes significant only when it is combined with high-powered analytics. To surmount the challenge of linking and correlating different data types, analysts need to be very vigilant and regular, alongside incorporating ultra sophisticated machinery.