Data Analyst vs. Data Science: Which Career is Right for You?
The Learning Hour* – Week 7 : Data Analyst vs Data Scientist
Posted by Ashish Agarwal
Data is the new oil and a lot of new job profiles revolve around it. This is a trend that is hard to reverse in the near future.
There are two job profiles in this domain that seem to cause some bit of confusion in our minds.
Most people wonder “What is the difference between a Data Analyst and a Data Scientist?”
Let us help to resolve this query here.
While there are some similarities between them, the two roles differ in a lot of aspects.
As the name suggests, both these roles require undertaking data cleansing and processing as well as visualization.
In both these roles, you need to be well versed with lot of data analysis techniques and tools like Excel, R, Python, SQL etc.
What are the differences?
- Data Analysts analyse trends to find meaningful information on past empirical data-sets while Data Scientists work to predict future outcomes based on past data trends
- A Data Analyst uses R/SAS tools for processing data while a data-scientists needs to work on advanced programming using Machine Learning and AI algorithms to process data.
- A Data Analyst does NOT require advanced knowledge of statistical tools and techniques while a Data Scientist definitely needs to be an expert in predictive modelling.
- A Data Analyst role gets paid less and also requires les experience than a Data Scientist.
So as you can see, there is quite of bit of difference a Data Analyst and a Data Scientist.
You may wonder, what is a better career for you?
Well, we don’t see this as a choice between a Data Analyst or a Data Scientist role.
We firmly believe that you need to have the skills of both Data Analyst and Data Scientists to become successful in this profession.
In fact, a great Data Scientist will also be a good Data Analyst and vice versa.
So both skills are quite complementary in nature.
However, most professionals would first be a Data Analyst in the early part of their careers and then gradually move on to the Data Scientist role.
So the natural evolution of a career will be from a Data Analyst to a Data Scientist.
Does this make sense?
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