Data Science Vs Data Analytics: Key Difference

Once you can define clearly the differences between data science and data analytics. Also, you can identify which will be fitted for you.

To determine which path is best as per your personal and professional goals, you should consider the following factors to decide which is better for you:

• Both data analytics and data science are similar but the main difference between data analytics and data scientists is their educational qualifications. A data analyst’s job is to examine large datasets to determine trends and patterns so that strategic decisions can be taken for businesses. To become a data analyst, you typically required an undergraduate degree or an advanced degree in science, technology, engineering, mathematics, or analytics. In data scientists, the main role is to design and construct new processes for data modeling. But to become a data scientist you should attain a master’s degree in data science. Although no matter what your educational background is right now, you can shape your future by learning new techniques and skills. So, if you have to decide which is better, you can learn it by considering which educational degree is required to become a data scientist or data analyst.

• The other factor which can be considered is what are your interests? Data analysts love numbers, statistics, etc. and they should have an in-depth understanding of the industry they work in. Whereas data scientists are fond of data, mathematics, statistics, computer science, and knowledge of the business world. So, if your interest matches with mentioned features, then you determine data science or data analysis, is a better career for you.