Big Data vs Analytics

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There is a common confusion about analytics and Big Data. What exactly is the difference between Big Data and Analytics? And if there is a difference, what is then Big Data Analytics?

Big Data simply is a catch-all term used to refer to multiple things – Big Data Collection, Big Data Storage, Big Data Processing, Big Data Reporting, Big Data Analysis, and so on. The enormous increase in the amount of data that is being generated, which itself is because pretty much everything we do is now being captured as data, has led to a need for much more robust and sophisticated infrastructure and systems requires to process the data. There are multiple tools and technologies developed to efficiently store, process, and retrieve these vast volumes of data, and all of these are part of the Big Data landscape

Within Big Data, there is also business intelligence, reporting, and analytics, performed using Big Data technologies. So Analytics is one part of what is enabled with Big Data technology. However, analytics is performed on datasets of all sizes, big or not. Of course, dealing with very large datasets with a variety of different types of data poses its own specific challenges, so there is some specialized expertise required to perform analytics on Big Data.

At every stage of the data mining process, starting from collection through analysis, there a variety of new technologies developed to manage Big Data volumes, and therefore there are multiple specialized job roles within the Big Data sphere of work. A lot of job roles are also heaving focused on IT skills, especially as related to data storage, processing, and querying.

If you are looking to build a career in this industry and are wondering – Big Data or Analytics: the answer is really both. It is important to have a solid base of analytics knowledge and statistical and predictive modelling skills to work in analytics. It is also increasingly becoming important to have knowledge of Big Data technologies like Hadoop for distributed computing, and MapReduce for efficient querying, as well as more specialized analytics software packages built for handling Big Datasets.

The key is in having a combination of skills that will give you the edge as this whole Big Data and Analytics industry evolves. We don’t know what the future has in store, so its best to keep your skill set updated with what is in demand in the industry.

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