Data Analytics vs. Data Science

We live in a data-driven world, and fields like data analytics and data science are becoming increasingly popular. Although the terms may sound similar and are often used interchangeably, they are not the same. Understanding these differences will help you make informed decisions, both with your study plans and career goals.

Data plays an important role in the success of businesses. With most companies having an online presence, they rely on vast quantities of data to scale up and make an impact. These insights power data-driven decisions, helping companies optimise their processes and also enhance customer experience. For example, Amazon uses its massive customer purchase data to help users decide what to buy next. This Recommendation-Based System (RBS), a data science model, helps Amazon generate a significant share of its annual sales (source: ProjectPro). From basic customer information to detailed user preferences, data is collected extensively, and it holds immense value.

In this article, we’ll explore:

• The key differences between data analytics and data science
• What is taught in Data Analytics vs Data Science
• top courses and universities to study these subjects
• and the career opportunities in each field

We hope that clarifying the difference between these two fields will enable Indian students to make an informed decision about their study plans. Choose the path that is right for you.

What is Data Analytics?

Data Analytics is the process of analysing and interpreting existing, structured data to derive actionable insights and patterns. Daya Analysts try to answer specific questions that support decision-making for businesses. 

What do Data Analysts do?

A data analyst's work typically involves making sense of existing data to find answers to specific questions for the business. They use mathematical and statistical techniques to explore data, find trends and patterns and understand the correlation between different variables and their outcomes. Finally, they use tools like Power BI or Tableau to create reports, charts and dashboards to convert their learnings into a format digestible to even non-technical individuals. They should have basic programming skills.

Data Analysts:

• Compile and clean data
• explore it to discover patterns and trends using mathematical and statistical techniques
• summarise and visualise data
• understand the correlation between different variables and their outcomes

Key skills and tools for Data Analysts

For efficient data analysis, you need strong analytical skills and communication skills to convey insights to non-technical stakeholders and clients effectively. Technical skills required for data analysis include Python and R, and SQL for database management. Some analysts also use specialised software such as SAS for statistical analysis and predictive modelling. Tableau, Microsoft Excel, Google Looker Studio and Microsoft Power BI are data visualisation tools commonly used by data analysts to visualise their findings. MySQL, PostgreSQL and Snowflake are the data management tools used by data analysts.

Here's a real-life example: Healthcare systems can analyse past infection records and current patient data to assess the likelihood of a rise in seasonal infections in a specific region using predictive analytics techniques.

What is Data Science?

Data Science is the practice of using Mathematics, AI, Statistics and Computer Engineering techniques to process raw or complex data to build predictive models and develop algorithms. It is also used to generate meaningful insights and patterns.

What do Data Scientists do?

While data analysis involves exploring existing, structured data to find answers to business questions, a data scientist is involved in transforming raw data into a suitable format for analysis. This raw data will be unstructured and messy. Using predictive data models and algorithms, a data scientist will then be able to forecast future trends or develop the algorithm itself to solve complex problems. 

Data scientists:

• Transform raw, complex data into a form suitable for analysis
• Use this analysis to build data models that can make predictions
• Analyse the performance of these models using performance metrics
• Provide recommendations based on the analysis of historical data.

Key skills and tools used in Data Science

A Data Scientist’s skills are an advanced version of the Data Analyst’s. They should have expertise in machine learning, big data handling, algorithm development, and data engineering. They should be able to program in Python or R to develop complex models and frameworks. Pandas, NumPy, and Scikit-learn are popular Python tools that data scientists use to make sense of large amounts of data. They also use special tools to handle complex tasks—like TensorFlow and Scikit-learn for teaching computers to make predictions, and Hadoop and Spark for working with really large datasets.

Data Science vs Data Analytics: A Detailed Comparison

The difference between data analysis and data science is based on their primary objective. They also differ in the subject focus, analytical approach, techniques used and the knowledge and skillset required.

What will you learn as part of a Data Analytics course?

Some of the topics covered as part of the Data Analytics course include:

1. Big data analytics
2. Data mining
3. Information visualization
4. Data in society
5. Information reporting and presentation
6. Python
7. Application of data analytics and development
8. Data ethics
9. Statistical modelling
10. Software tools/programming languages such as Knime, Tableau, Hadoop or Spark

What will you learn as part of the Data Science course?

Some institutions offer an optional 1-year-long work placement. For the dissertation, you will deal with real-world problems through cutting-edge research.

1. Machine learning
2. Big data analytics
3. Deep learning algorithms
4. Natural Language Processing (NLP)
5. Data Ethics and Privacy
6. Artificial intelligence
7. Computational modelling
8. Fundamentals of data science methods
9. Algorithms and data structures
10. Business intelligence and decision making

Want to study Data Science in the UK? Explore our article for some of the popular institutions for studying a Master's degree in the UK.

Where can you study Data Analytics abroad?

Top universities for Data Analytics (including business analytics) are:

1. Massachusetts Institute of Technology (MIT Sloan)
2. University of California, Los Angeles (UCLA Anderson)
3. ESSEC Business School (France)
4. HEC Paris (France)
5. London Business School
6. Columbia Business School
7. Duke University (Fuqua School of Business)
8. Imperial College Business School (UK)
9. ESCP Business School, Paris
10. IE Business School, Spain

These universities are featured in the QS Business Masters Rankings 2025 for Business Analytics.

The most popular courses and institutions among Indian students for Data Analytics courses include:

• MSc in Data Analytics Engineering
• MSc in Data Analytics
• MSc in Business Analytics – Big Data Analytics
• MSc Big Data Analytics
• MSc Advanced Computer Science (Data Analytics)
• Ontario College Graduate Certificate in Big Data Analytics
• MSc in Applied Modelling and Quantitative Methods – Big Data Analytics
• Post Degree Diploma in Data Analytics
• Master of Business Data Analytics

Universities popular among Indian students for Data Analytics courses include:

Where can you study Data Science abroad?

Top universities for Data Science include:

1. Massachusetts Institute of Technology (MIT)
2. Carnegie Mellon University
3. University of Oxford
4. University of California, Berkeley (UCB)
5. Nanyang Technological University, Singapore (NTU Singapore)
6. Harvard University
7. National University of Singapore (NUS)
8. ETH Zurich
9. Yale University
10. University of Toronto

These universities are listed in the QS World University Rankings by Subject 2025: Data Science and Artificial Intelligence, 2025.

The most popular courses and institutions among Indian students for Data Science courses include:

• Master of Data Science
• Master of Data Science and Innovation
• Master of Engineering in Data Science and Analytics
• MSc in Data Science and Analytics
• Ontario College Graduate Certificate in Artificial Intelligence and Data Science
• MSc Data Science and Business Analytics
• Master of Science in Data Science with professional placement
• MSc Big Data Science
• Master of Professional Studies in Data Science

Universities popular among Indian students for Data Analytics courses include:

Check out our article for details about more universities for studying Data Science MS in the USA and MS in Data Science in Canada.

Career and salary outlook

Both Data Analysis and Data Science jobs are in demand and have immense salary potential. According to the World Economic Forum's Future of Jobs Report 2025, the technology trend that is expected to drive business transformation includes AI and information processing technologies such as big data, VR and AR.

Career opportunities after completing a Data Analytics course

Common career paths for those with a degree in Data Analytics include:

• Data Analyst
• Business Analyst
• Market Research Analyst
• Financial Analyst
• Healthcare Analyst

Individuals in the Data Analyst role earn an average base salary of USD 83,991 per year (indeed.com). The National Association of Software and Services Companies (NASSCOM) predicts that the analytics industry in India will reach USD 16 billion by 2025.

Career opportunities after completing a Data Science course

For those with a degree in Data Science, the career opportunities are more specialised and technical. It includes:

• Data Scientist
• Data Architect
• Data Engineer
• Risk Management Analyst
• Machine Learning Engineer

According to the U.S. Bureau of Labour Statistics, the 2024 median pay for Data Scientists in the USA was USD 112,590 per year. The job outlook for 2023-33 is predicted to be much faster than the average at 36%. In India, the Data Science market is estimated to reach USD 2,551.2 Million by 2033, exhibiting a CAGR of 18.91% from 2025-2033 (according to the International Market Analysis Research and Consulting (IMARC) Group). IMARC also states that South India is dominating the market.

Both Data Analytics and Data Science have an increasing scope in the current world, where every major business decision is data-driven. Head to our site to learn the details of the course and pick the best one for you!