Data analysts and data scientists define two of the most in-demand, high-paying jobs in 2022. Data Science and Data Analytics work with data but are different from each other. If you're interested in a career operating with big data and numbers, there are two paths you may want to choose —becoming a data analyst or a data scientist. 

Who are Data Analysts?

A Data Analyst is a trained professional who gathers data from multiple sources, organizes it, and performs analysis on it. Businesses induce data from log files, customer information, transaction data, etc. Data analysts' job is to convert these valid business data into actionable insights. Data analysts use data manipulation techniques to analyze and decipher complex data sets to help companies and organizations make better judgments.

Who are Data Scientists?

Data Scientists are experienced specialists who comprehend business challenges and possibilities and create the most suitable solution utilizing modern tools and techniques. They employ statistical methods, data visualization techniques, and machine learning algorithms to make predictive models and solve challenging problems. Data Scientists emanate meaningful information from messy and unstructured data and communicate necessary information and understandings to business executives and stakeholders.

Data Analyst vs. Data Scientist - Differences


Data Analyst

1. Manage data from databases and warehouses, filter, and clean it.

2. Write complex SQL queries and scripts to collect, store, manipulate, and retrieve data from RDBMS such as MS SQL Server, Oracle DB, and MySQL.

3. Create various operating charts and graphs using Excel and BI tools. 

4. Point ot trends and patterns from complex datasets.

Data Scientist 

1. Conduct ad-hoc data mining and gather extensive sets of structured and unstructured data from several references.

2. Utilize different statistical methods and data visualization techniques to create and evaluate developed statistical models from extensive volumes of data.

3. Create AI models operating various algorithms and in-built libraries.  

4. Automate tiresome tasks and develop insights utilizing machine learning models


No special educational qualification is required to become a data analyst or a data scientist. It would help if you held a degree in any relevant field, engineering in computer science, information technology, electrical or mechanical engineering. One can also be a graduate in mathematics, statistics, or economics. 


Data Analyst

1. Good experience in statistics and probability

2. Knowledge of Python programming and SQL

3. Analyzing data with MS Excel and building reports using Tableau

4. Data wrangling

5. Exploratory data analysis

Data Scientist 

1. A strong foundation in calculus, linear algebra, statistics, and probability. 

2. Well-versed in Python, SQL, R, SAS, MATLAB, and Spark.

3. Data visualization using Power BI and Storytelling using Tableau 

4. Data wrangling and data modeling

5. Machine learning and cloud computing

Salary Insights

As per research by glassdoor, a Data Analyst earns nearly $70,000 per annum In the United States. 


As per research by glassdoor, a Data Scientist in the US earns $100,000 per annum.

Start your career with EdtiaTake the first step on your career path in data science by achieving a Data Analyst Professional Certificate. To know more about the route from data analyst to data scientist, including recommendations for skills, courses, and guided projects, check out our Data Science Career Learning Path.


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