With the advent of increasing digital technology companies have to collect huge amount of data. It is difficult to manage such huge amounts of data with normal analytical tools. This has given rise to some stronger analytical tools which are capable of making sense out of this pile of data. It has resulted in the birth of big data analytics, which has emerged as a necessary tool requiring specialized skills.
Big Data is getting more popular by the second. Its annual Growth rate is predicted to be US$ 32.4 billion in 2017. Some reports also suggest that a whole lot of data considered asbig datawill be shifted to the cloud which will change the old datacenter revenue for storage. Big data is not a neat, organized data to look at as it is full of raw data coming from a variety of sources formatted differently.
Data is pulled from all types of medium-external as well as internal sources. It adds value to itself when varieties of data sources are able to overlay to see the bigger picture that comes out of those data sets. From individual data, the information that it withholds cannot be understood. So the related data needs to be seen to understand the information allowing a user to run his business effectively. Big data is not of any value till the time Data Scientists decipher, analyze and explore the data.;
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