What is the meaning of data science and how is it different from data analytics?
Asked by Manoj Soni over 1 year ago
There are a lot of things that are often considered as same when they are not, such as MiM and MBA, Stock Market and gambling and many more. One of those things is data science and data analytics. Many students still consider these as the same thing and often say that they are going to become a data analyst when they are actually pursuing a data scientist course.
In order for you to not do these kinds of blunders, I have mentioned some key differences between a data analyst and a data scientist. So let’s get started with them:
In data science, you apply various algorithms, processes., and scientific methods from structured and unstructured data to derive meaningful insights from them. But in data analytics, you process raw data to arrive at the conclusions.
Data science is a much more broad scope with many branches and fields. Data analytics has a much narrower scope and is a subset of data analytics.
The knowledge and skills needed in data science are much more in-depth than in data analytics.
Machine learning is used in data science and sometimes it is an essential part of various data science tasks. But data analytics has no relation to machine learning.
Some major fields where data science is used are Machine learning, AI, search engine engineering, and corporate analytics. Healthcare, gaming, and travel are some major fields where data analytics is used.
So, these were some major differences between data science and data analytics, there are others as well but for the time being, these are sufficient. But no matter what differences are there between the two fields, both data science and data analytics are two sides of the same coin.
Would you like to tell me how many of these were you already aware of and how many were new to you?
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