Actually, I'm BCA student. Can I become data scientist? What should I do to become a data scientist?

Data scientists are a new breed of analytical data expert who have the technical skills to solve complex problems and the curiosity to explore what problems need to be solved. There part mathematician, part computer scientist and part trend-spotter. And, because they straddle both the business and IT worlds, there highly sought-after and well-paid. Whowouldntwant to be one? There also a sign of the times. Data scientists were't on many radars a decade ago, but their sudden popularity reflects how businesses now think aboutbig data. That unwieldy mass of unstructured information can no longer be ignored and forgotten. Its a virtual gold mine that helps boost revenue as long as there's someone who digs in and unearths business insights that no one thought to look for before. Enter the data scientist. Where did they come from? Many data scientists began their careers as statisticians or data analysts. But as big data (and big data storage and processing technologies such as Hadoop) began to grow and evolve, those roles evolved as well. Data is no longer just an afterthought for IT to handle. Its key information that requires analysis, creative curiosity and a knack for translating high-tech ideas into new ways to turn a profit. The data scientist role also has academic origins. A few years ago, universities began to recognize that employers wanted people who were programmers and team players. Professors tweaked their classes to accommodate this and some programs, such as the Institute for Advanced Analytics at North Carolina State University, prepared to churn out the next generation of data scientists. There are now more than 60 similar programs in universities around the country.

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There's is no right path to become a data scientist. You can approach data Science from many angles as long as your motivation to learn stays on the same level. That said, you should have a specific foundation to grow and cultivate your data-Science abilities. Some experience in coding is much recommended, also an analytical mind and a passion for numbers. But keep in mind that it doesn’t mean you need to have a degree in computer Science or Maths. As for the necessary background, I won't say anything that hasn’t already been stated here. To become a data scientist, you need to have at least some experience in the following programming languages and software. Python or R language (statistical computing) Database language, I. e. SQL SAS (statistical language) Apache Hadoop or Cluster MapReduce, or other similar frameworks Apache Storm (for stream data processing) When you’ve acquired the necessary base, you can more or less jump into the depths of big data and pretty much learn the intricacies of data Science on-the-go, as practical training brings the most efficient results. There are quite a few websites around the Internet from where you can download big datasets for your first data-Science training sessions. Check out sites like Reddit, Amazon, or Google Books. But the truth is, working and learning with data widely available for the public can be boring and tedious. After all, you’re working with data that essentially means nothing to you. Thus I would argue that the best way to learn data Science, aside from acquiring your base, is having access to data that is interesting to you, figures that you would like to grasp meaning from.

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