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As we all know the time is of DATA, there is no doubt in the mind when I say the boom in the data industry has driven and taken the demand for data science, data Analyst and Data engineers to the next level, across all industry verticals. There are job openings for data scientists, data engineers, and data analysts. And there seems to be a lot of confusion and lot many different opinions among people regarding the roles and skillsets driving this field. Here we will mostly discuss two major job titles, Data Scientist and Data Analyst.

Let us Understand the Main Difference Between Data Scientist and Data Analyst

I know many of you may not convince with this but yes, there are no defined skill-sets that can distinguish between the role of a ‘Data Scientist’ and ‘Data Analyst’. This is mainly because most of the companies have their own definition and role descriptions. In fact, different companies have different definitions for both these roles, and there is a lot of grey area in between the two job titles. Broadly analyzing, a Data Scientist is a professional who combines data handling and data visualization with sound business understanding to make smart business decisions.

We’re living in a time of marvelous opportunity, especially for those who work in the tech industry. With so many evolving technologies, skilled professionals can extend their knowledge to become specialists in several fields or transition into a new field. This is particularly true of Big Data, where the types of jobs are increasing as the rate of data generated each day increases at an amazing pace. Even as we generate unprecedented amounts of data in 2018, IDC predicts we will generate approximately 440 times more information by 2020. All that data must be stored in scalable and cost-effective data platforms, while still being accessed, analyzed, and put to use. And it’s the Big Data professionals who make all of that happen, meaning today’s organizations have a dire need for Big Data professionals, including data scientists, data analysts, data engineers, and developers, and systems administrators and managers. For those with the right skill set and certifications, the market offers plenty of job opportunities and attractive salaries packages. According to Glassdoor, there are almost 49,000 Big Data jobs that need to be filled, isn’t this superbly amazing!

We all know that data scientists are in high demand. In fact, Amazon says that job opportunities for these experts have grown by 505% over the last 5 years. With the Internet of things producing more data than ever before, it’s easy to see why all organisations want people who can make sense of big data to drive them to success. But what does this mean for market researchers? Can data science really replace them all together? Per Statista, the big data market is growing rapidly, with $42 B USD revenues in 2018 and a massive increase to an expected $1.89 B in 2019. Corporations are adopting new technologies to help manage integration and draw insights from big data. In the telecommunications industry alone, around 94.5 per cent of respondents representing the telecommunications industry stated that their organization currently used big data technology as of 2018.

The market researchers are still essential in understanding the context of the information provided by data scientists, and to interpret the ‘what’ from the ‘why’. Ben Page, chief executive of Ipsos MORI goes on to explain how observational research is still essential, using a real-life study conducted for a global pet food manufacturer as a case in point.

If you are thinking of becoming a certified SAS programmer, you are on the right path to become a shining star in the most in demand industry for the 21^st century. However, it a valid concern on how to pass and become a SAS Certified Programmer.