Data Analyst Vs. Data Scientist: What's the Difference?
Data Scientist and Data Analyst are two terms that are often considered to be the same. You might be wondering, "What's the key difference between a Data Scientist and a Data Analyst?" They are both professionals who use data to help make decisions. However, there are some key differences in their job titles, which we will explore here.
When choosing between a Data Scientist or a Data Analyst, there are many factors to consider. A lot of people have their own opinions about the two roles, but it's important to remember that they are very different positions that require different skill sets and responsibilities.
In this article, we will discuss the major differences between Data Analysts and Data Scientists. Before that, let us see what functions they perform.
Data Analyst
A Data Analyst is someone who looks at the raw data and makes sense out of it by finding patterns in it and turning that into insights for decision-makers. They also work on finding the right questions that need answers and then finding the right datasets to answer them.
Main Duties:
Common data scientist tasks include:
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Data Cleaning
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Perform Data Analysis
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Create Data Visualizations
Various Job Roles:
Depending on the industry, the Data Analyst may get a job title of:
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Business Analyst
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Operational Analyst
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Database Analyst
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Business Information Analyst
Regardless of the name, a data scientist is a person who can fit into multiple roles and teams to help others make better data-driven decisions.
Data Scientist
Data scientists work on algorithms by using various techniques such as predictive modeling, data mining, machine learning, and more. These techniques are used to predict future events based on historical data. They use a combination of statistical analysis, mathematical modeling, computational modeling, and programming to develop a new methodology or technique for solving a business problem.
Main Duties:
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Collecting, cleaning, processing of raw data, and writing programs to automate them.
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Develop predictive models & Machine Learning (ML) algorithms for big data
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Development of tools and processes for monitoring and analyzing the correctness of data.
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Create data visualization tools, reports & dashboards.
Differences Between Data Scientist and Data Analyst
Data Scientist and Data Analyst are two different jobs with different roles and responsibilities. Let us look at the key differences.
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Features |
Data Scientist |
Data Analyst |
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Responsibilities |
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Education |
Any bachelor’s degree in engineering, mathematics, statistics, & economics. |
Any bachelor’s degree in engineering, mathematics, statistics, & economics. |
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Skills |
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Salary |
As per glassdoor.com, the average salary for Data Scientist in India ₹10,00,000/year & in US $1,17,212/year |
As per glassdoor.com, the average salary for Data Analyst in India ₹5,94,500/year & in US $69,517/year |
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Career Growth |
You can get into the entry-level of this job role and upscale the skills by advanced Data Analysis techniques |
This is the most wanted job role in many companies. There is a large scope to skill up and get into the role of “Research Scientist” |
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Job Search |
Naukri: 25043 |
Naukri: 14280 |
Final Thoughts
There are significant differences between data science and data analysis. For business professionals looking to better understand data and how it is used in an organization, it is important to understand the key concepts, systems, and methods that underpin both areas.
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