Ganesh Lala

All by myself

It is just not you but there are many other people in this world who get confused to differentiate between data science and data analytics. Some consider it same and some believe in the fact that there is at least little difference between the two if not many. Here we can say that if you consider data science like a house which holds the methods and tools then data analytics can be defined as the particular room of that house and it is closely related and partially matches the overall features of data science. 

If data science is like an umbrella term which includes data analytics, machine learning, data mining, and many other similar disciples. You can consider the data scientist as the person who can forecast about the future depending on the shown pattern of the past. On the other hand, the data analyst will be responsible for the extraction of meaningful insights from different sources of data. 

Data science goal is to ask the correct set of questions while for data analytics it is to find actionable data. Data science is Macro while Data analytics is Micro. You can find the role of Data Science in Machine learning, AI, Corporate analytics and search engine engineering. For Data analytics you can see its application in Healthcare, travel, and gaming industry where there is a need for immediate data. To get a better idea about the matches and differences between Data science and data analytics we recommend you to get in touch with the professionals who all are working in this field. They can give you a practical example for the same making your understanding easy and simple for you.  But will advise you to consider both these fields together to make the best application in the big data industry.

Item added successfully. Go to cart for checkout.
Accept Reject