What is the data analytics course?

A Data Analytics course teaches students how to collect, process, and analyze large sets of data to uncover patterns, insights, and trends It covers essential skills like statistics, data visualization, programming (e g , Python, R), and the use of tools such as SQL, Excel, and Power BI

Which course is best for data analytics?

The best courses for data analytics include:Bachelor's in Data Science: A comprehensive program covering statistics, programming, machine learning, and data visualization Master's in Data Analytics: Advanced studies focusing on data analysis techniques, big data, and predictive modeling Online Certifications (e g , Google Data Analytics, Coursera, edX): Short-term programs that provide practical skills in tools like Excel, SQL, Python, and Tableau MBA in Business Analytics: Combines business strategy with data analysis to make informed decisions

What is the role of data analytics?

The role of data analytics is to transform raw data into meaningful insights that help organizations make informed decisions It identifies trends, patterns, and correlations within data to improve business operations, optimize strategies, reduce risks, and drive growth

Is data analytics a good career?

Yes, data analytics is a good career It offers high demand, competitive salaries, and diverse opportunities across industries like finance, healthcare, and technology As businesses increasingly rely on data-driven decisions, skilled data analysts are essential, making it a rewarding and future-proof career choice

Data Analytics Course: Admission, Fees & Careers

A Data Analytics Course is a professional or academic programme that teaches students how to collect, clean, analyse, interpret, and visualise data to help organisations make informed business decisions. The programme covers Python, SQL, Excel, Tableau, Power BI, statistics, and machine learning fundamentals, preparing graduates for careers in finance, healthcare, IT, retail, and consulting.

Today, organisations generate massive amounts of data every second, but raw data has little value unless someone can transform it into meaningful insights. This is where data analytics professionals play a crucial role.

If you enjoy solving problems, working with numbers, identifying trends, and making data-driven decisions, a Data Analytics Course can open doors to one of the fastest-growing careers worldwide.

What is Data Analytics?

Data Analytics is the process of collecting, organising, cleaning, analysing and interpreting raw data to uncover meaningful insights that help individuals and organisations make informed decisions. By using statistical methods, programming languages, and visualisation tools, data analytics transforms complex datasets into actionable information that improves efficiency, predicts trends, and solves business problems.

Types of Data Analytics

Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics

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Data Analytics Course Levels

Programme Level	Programme Examples	Typical Duration
Undergraduate Programmes	BBA in Data Analytics BSc in Data Analytics BTech with Data Analytics Specialisation	3–4 Years
Postgraduate Programmes	MSc in Data Analytics MBA in Business Analytics MSc in Data Science (Analytics Focus)	1–2 Years
Certificate & Diploma Programmes	Certificate in Data Analytics Diploma in Data Analytics Industry-Oriented Professional Certification Courses	3–12 Months

Eligibility Criteria

Passed 10+2 (Class 12) or equivalent from a recognised board.
Students from Science, Commerce, or Arts streams are generally eligible (subject to university guidelines).
Must meet the minimum aggregate marks required by the respective university.
Admission may be based on merit or the university's admission process.
Basic knowledge of mathematics and computers is beneficial but not mandatory.
An interest in data analysis, problem-solving, and technology is an added advantage.

What are the Core Subjects in Data Analytics Course?

Foundation Subjects

Statistics and Probability
Mathematics for Analytics
Business Fundamentals

Technical Subjects

Programming with Python and R
Database Management Systems (DBMS)
SQL and NoSQL Databases
Data Structures

Analytics & Data Science

Exploratory Data Analysis (EDA)
Data Mining Techniques
Predictive Modelling
Machine Learning Basics

Data Visualisation & Storytelling

Data Visualisation Techniques
Data Storytelling
Dashboard Design
Visualisation Tools (Power BI, Tableau, and more)

What Will You Learn in a Data Analytics Programme?

Subject	Skills Learned
Python	Programming
SQL	Database
Statistics	Analysis
Excel	Reporting
Tableau	Visualisation
Power BI	Dashboards
Machine Learning	Prediction
Business Analytics	Decision Making

What are Common Tools Used in Data Analytics Course?

Microsoft Excel
SQL (Structured Query Language)
Python
R Programming
Tableau
Microsoft Power BI
Google Looker Studio
Apache Spark
Apache Hadoop
Jupyter Notebook
SAS
SPSS
Microsoft Azure
Amazon Web Services (AWS)

Admission Process for Data Analytics Course

Complete the Application Form: Fill out the online or offline application form with accurate personal and academic details.
Submit Required Documents: Upload or submit documents such as Class 10th & 12th mark sheets, passport-size photographs, identity proof, and other required certificates.
Document Verification: The university verifies your academic records and supporting documents.
Merit Selection: Eligible candidates are shortlisted based on the university's admission criteria and merit.
Pay the Admission Fee: After selection, pay the prescribed programme fee to confirm your seat.
Admission Confirmation: Once the fee payment and document verification are completed, your admission is officially confirmed.

Data Analytics Course Fees

College Type	Average Data Analytics Course Fees (Total)
Government Colleges	₹20,000 – ₹2,00,000
Private Colleges/Universities	₹2,00,000 – ₹8,00,000
Private Deemed Universities	₹4,00,000 – ₹10,00,000
Online/Distance Programs	₹20,000 – ₹2,00,000
Certificate Courses	₹10,000 – ₹1,00,000
Diploma Courses	₹30,000 – ₹2,00,000

Data Analytics vs Data Science

Data Analytics Course	Data Science Course
Analyses existing data to find insights	Builds predictive models and AI solutions
Focuses on business decision-making	Focuses on solving complex data problems
Uses tools like Excel, SQL, Tableau, and Power BI	Uses Python, R, Machine Learning, and AI
Creates reports and dashboards	Develops algorithms and predictive models
Best for business intelligence and reporting	Best for AI, automation, and advanced analytics

Career Opportunities After Data Analytics Course

A Data Analytics course opens the door to diverse and high-demand career opportunities-

Data Analyst
Business Analyst
Marketing Analyst
Business Intelligence (BI) Analyst
Healthcare Data Analyst
Supply Chain Analyst
Operations Analyst
Data Visualisation Specialist
Customer Insights Analyst

Industries Hiring Data Analytics Graduates

Healthcare
Finance
Retail
Manufacturing
Government
Consulting
EdTech
Banking
Insurance
E-commerce
IT
Telecom
Automobile

Importance of Data Analytics

In today's digital world, data has become one of the most valuable assets for businesses and organisations. As industries increasingly adopt artificial intelligence (AI), machine learning, cloud computing, and big data technologies, the demand for skilled data analytics professionals continues to rise.

Why Data Analytics Matters

Supports Better Decision-Making
Improves Business Performance
Enhances Customer Experience
Identifies Market Trends
Detects Risks and Fraud
Boosts Career Opportunities
Powers AI and Automation

The global data analytics market is projected to grow from USD 104.39 billion in 2026 to USD 495.87 billion by 2034, at a CAGR of 21.5%, highlighting the increasing adoption of analytics across industries.

Why Choose TMU for a Data Analytics Course?

As data becomes the backbone of modern businesses, choosing a university that offers practical exposure, industry-relevant skills, and career support is essential. Teerthanker Mahaveer University (TMU) prepares students for the evolving field of data analytics through a curriculum that combines technical knowledge with real-world applications. Here's why TMU stands out:

Industry-Oriented Curriculum
Hands-on Learning Experience
Learn In-Demand Analytics Tools
Experienced Faculty and Mentorship
Industry Exposure and Internships
Strong Placement Support
Modern Learning Infrastructure
Multidisciplinary Learning Environment

Conclusion

A Data Analytics Course is an excellent choice for students who want to build a future-ready career in today's data-driven world. As businesses across industries increasingly rely on data to make strategic decisions, the demand for skilled professionals continues to grow. By learning in-demand tools such as Python, SQL, Power BI, Tableau, and data visualisation techniques, students can explore rewarding career opportunities in IT, finance, healthcare, e-commerce, consulting, and many other sectors.

FAQ

Q1. What does data analytics do?

Answer: Data analytics is the process of collecting, cleaning, organising, and analysing data to identify patterns, trends, and insights. Businesses use data analytics to make informed decisions, improve customer experiences, increase efficiency, reduce costs, and predict future outcomes.

Q2. Is data analytics a good job?

Answer: Yes, data analytics is one of the fastest-growing and highest-demand careers worldwide. Organisations across healthcare, finance, IT, retail, manufacturing, education, and e-commerce rely on data analysts to make data-driven decisions. It offers competitive salaries, excellent career growth, and opportunities to work in multiple industries.

Q3. What are the top 3 skills for a data analyst?

Answer: The three most important skills for a data analyst are:

Data Analysis & Statistics
SQL & Databases
Data Visualisation

Q4. Who earns more, CA or data analyst?

Answer: Both careers offer excellent earning potential, but salaries depend on experience, industry, and expertise. Chartered Accountants (CAs) often earn more in finance and auditing roles, while experienced data analysts, data scientists, and analytics managers in technology and multinational companies can earn equally high or even higher salaries.

Q5. Which data analytics tools would you recommend for beginners?

Answer: Beginners should start with:

Microsoft Excel
SQL
Microsoft Power BI
Tableau Public
Python (Pandas, NumPy, Matplotlib)
Google Sheets
Jupyter Notebook

Q6. Is coding required for data analytics?

Answer: Not always. Beginners can start with Excel, Power BI, and Tableau without extensive coding. However, learning SQL and Python can significantly improve your career opportunities and analytical capabilities.

Note:
This content gives an overview of the programme and is for educational purposes only. For updated admission guidelines and counselling support, please connect with our Counsellor Team.