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The development of every new technology comes with the production of enormous raw data so-called “big-data”. With the continuous expansion of data in all domains, the analytics is merging as the latest buzz in the market. The job of analyzing raw data is a big challenge and that is the reason data scientist jobs have skyrocketed. All the big or raw data available are not useful for analysis and thus for decision making (Acharya & Kauser,2016). The role of data analytics becomes crucial to transforming this collated data into pieces of value-added information.

The major industries of the analytics usage are Retail, ITES (Information Technology Enabled Services), Telecom Services, BFSI (Banking, Financial Service and Insurance), and FMCG (Fast Moving Consumer Goods)(Banerjee et al.,2013). The research published by Harvard Business Review in the year 2012, gave data scientists the title of "best job of the 21st century" and this title still holds its value in the market. In glass door’s best jobs in America for 2018, the data scientist job was ranked among the top five jobs determined on factors like annual salary, job satisfaction, and job openings. It is well-established fact that how data scientists have helped big companies like LinkedIn, Amazon, Facebook, Walmart and many others to unlock the real value from raw data.

In the current scenario, there is a huge demand for analytical professionals across the globe. Along with this increasing demand in the analytical industry, there is a severe shortage of analytical professionals. The analytics and big data industry are evolving at a faster pace and the required skills and expertise are still lacking. The predictions by McKinsey Global Institute mentions that there is a huge shortage of data scientists in the US alone by 2018.

In India, the market for data analytics is huge and according to a study by Analytics India Magazine and AnalytixLabs titled 'Analytics India Industry Study 2017,' the analytics industry in India is expected to double by the year 2020. The article published in the economics times mentions that as per the National Association of Software and Services Companies (NASSCOM) the big data analytics is supposed to reach $16 billion by 2025. According to the Forbes magazine article, the jobs for data scientists will rise up to 28% by 2020 as per IBM.

The field of data science is a long-term career path and a lucrative field with plenty of jobs. With the continued lack of talent, the demand for the data scientist is likely to continue into the foreseeable future as well. To become a data scientist in the present scenario is not a tough nut to crack. In order to ensure value to your job profile the proper education and to beef up your existing skillsets is key to become a good data scientist. The article published by information week tells that there is a need for data science people to reshape their skillsets in order to reach their full potential.

At present, many data courses are available on the internet to learn and hone your skills in different analytics tools. The most lucrative analytics skills include SAS, R, Python, MapReduce, Apache Pig, Machine Learning, Apache Hive and Apache Hadoop, etc. The knowledge of one analytical tool is not enough, and it is falling out of fashion. There is a need to keep yourself always updated with new technology and tools to overcome the fear to get left behind in the world of analytics. There is lifelong learning necessity in the analytics field to fill the gap of lacking talent. Soon, the data science will dominate every aspect of the industry and thus will generate enormous opportunity for every data scientist. As every company is moving faster towards a data-based decision-making approach, the knowledge and skills of data scientists are required to leverage data for informed decision-making.