What is the difference between data science and data analytics?

| January 9, 2019

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One of the biggest jobs in the technological center is working with big data. There are plenty of roles within this sector and two of the most popular ones include data science and analytics. While a lot of companies tend to hire similar candidates for these roles, there is still a difference between the two. It is important that you understand the two roles before you choose a career path in either. If you’re looking to kickstart a career in the field of big data, then knowing the difference between data science and analytics is a good pointer to keep in mind. What is data science? Data science is a broader term for different methods and models used to get information. Under data science are the statistics, scientific methods and math along with other tools which can be used to manipulate and analyse data. If there is a process or a tool that can be used on data to analyse it and extract information from the same, then it falls under the umbrella of data science.

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Boost AI

Boost AI is a global machine learning company which helps companies to convert data into business decisions. The people behind Boost AI have many years of experience from Silicon Valley and a Ph.D in big data and machine learning. We help companies with problems such as: predicting sales of a store, predicting customer satisfaction level, and many other problems. Our models can be used in various industries such as grocery stores, banks, weather stations, traffic, telecommunication, utility, and many other industries. Boost AI is headquartered in Stavanger (Norway) with three employees and has an advisor which is number one in the world in competitive data science. Boost AI delivers services to the whole world.

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