If you enjoy working with numbers, solving problems, and using information to make better decisions, a career in data analytics may be a good fit. But choosing a degree can be confusing because there is no single college major required for every data analytics job.
A degree in data analytics, business analytics, statistics, computer science, mathematics, information systems, or data science can all provide relevant preparation. The best choice depends on the type of analytics work you want to do and whether you prefer business, statistics, programming, or more advanced technical work.
For someone who knows they want to become a data analyst, a data analytics or business analytics degree is often the most direct option. However, a statistics or computer science degree may be a better choice if you want to build deeper quantitative or programming skills.
What Is the Best Degree for Data Analytics?
The best degree for data analytics depends on your career goals.
A bachelor’s degree in data analytics is designed specifically around analyzing and interpreting data. A business analytics degree may be a better fit if you want to use data to solve business problems. A statistics degree can provide stronger preparation in statistical methods, while computer science can give you a deeper programming and technical foundation.
Here is how some of the most relevant degrees compare:
| Degree | Best For | Technical Depth | Common Areas of Focus |
| Data Analytics | Students seeking a direct path into analytics | Moderate to high | Data analysis, statistics, databases, visualization |
| Business Analytics | Students interested in business decision-making | Moderate | Business intelligence, reporting, forecasting |
| Statistics | Students who enjoy math and quantitative analysis | High | Probability, statistical modeling, regression |
| Computer Science | Students interested in programming and technical careers | High | Programming, algorithms, databases |
| Mathematics | Students who want a strong quantitative foundation | High | Mathematical modeling, statistics, quantitative reasoning |
| Information Systems | Students who want to combine business and technology | Moderate | Databases, systems, business technology |
| Data Science | Students interested in advanced analytics and machine learning | Very high | Programming, statistics, predictive modeling |
There is also considerable overlap among these fields. A data analyst with a statistics degree, for example, may perform many of the same duties as someone with a data analytics degree.
1. Data Analytics
A bachelor’s degree in data analytics is one of the most direct choices for someone who already knows they want to work with data.
Depending on the college, a data analytics curriculum may include courses in:
- Data analysis
- Statistics
- SQL and database management
- Data visualization
- Excel
- Python or R
- Business intelligence
- Data management
- Predictive analytics
The advantage is that you can develop several of the skills employers look for without having to piece them together from different areas of study.
Best for: Students who want a degree specifically designed to prepare them for data-focused roles.
For example, a student might complete a data analytics degree, build a portfolio of SQL and data visualization projects, and apply for entry-level positions such as data analyst, reporting analyst, or business intelligence analyst.
2. Business Analytics
Business analytics is another strong choice, particularly if you are interested in using data to answer business questions.
Instead of focusing exclusively on the technical side of data, business analytics programs often connect analytics with areas such as:
- Marketing
- Finance
- Operations
- Management
- Supply chain
- Customer behavior
Consider a retailer that notices declining sales for one of its product lines. A business analyst might examine sales, customer, pricing, and inventory data to determine what is happening and recommend a course of action.
That combination of data analysis and business decision-making is reflected in the work of business intelligence analysts. These professionals use data repositories, reports, dashboards, and trend analysis to help organizations make decisions.
Best for: Students who want to work with data but are particularly interested in how organizations use data to make decisions.
3. Statistics
A statistics degree can provide a strong foundation for data analytics because it teaches you how to collect, analyze, interpret, and draw conclusions from data.
Coursework may include:
- Probability
- Statistical inference
- Regression analysis
- Experimental design
- Statistical modeling
- Applied statistics
Statistics can be particularly useful if you are interested in research, healthcare analytics, market research, forecasting, or other quantitative fields.
The American Statistical Association maintains career resources for statisticians and data science professionals and emphasizes the role of formal education, professional development, and statistical knowledge in the field.
Best for: Students who enjoy mathematics and want a deeper understanding of the statistical methods behind data analysis.
One consideration is that a traditional statistics program may not teach as much SQL, database management, or data visualization as a dedicated analytics program. If you choose statistics, look for opportunities to add those skills through electives, projects, internships, or professional training.
4. Computer Science
Computer science may not sound like an obvious data analytics degree, but it can provide a strong technical foundation.
Computer science programs commonly cover subjects such as:
- Programming
- Algorithms
- Data structures
- Databases
- Software development
- Computational problem-solving
Those skills can be useful for data analysts who work with large or complex datasets.
A computer science degree can also give you flexibility if you eventually decide to move beyond traditional analytics into areas such as data engineering, machine learning, analytics engineering, or software development.
Best for: Students who enjoy programming and want the option to pursue more technical careers.
The tradeoff is that a computer science program may include substantial coursework that isn’t directly related to data analysis. If your only goal is to become a business-focused data analyst, a data analytics or business analytics program may provide a more direct curriculum.
5. Mathematics
A mathematics degree can prepare you for analytics by developing strong quantitative reasoning and problem-solving skills.
Depending on the program, you might study:
- Calculus
- Linear algebra
- Probability
- Mathematical modeling
- Statistics
- Discrete mathematics
A mathematics major can be especially useful for someone who eventually wants to work in a highly quantitative field.
However, students should look beyond the degree title when evaluating a mathematics program for an analytics career. If the curriculum contains little programming, database, or applied statistics coursework, you may need to develop those skills separately.
Best for: Students who enjoy mathematics and want a rigorous quantitative foundation.
6. Information Systems
Information systems sits at the intersection of business and technology, making it another possible route into analytics.
An information systems program may include:
- Database management
- Business intelligence
- Systems analysis
- Information technology
- Data management
- Enterprise systems
This can be particularly useful if you want to understand not only how to analyze data, but also how organizations collect, store, manage, and use information.
Best for: Students who want a combination of technology, data, and business.
7. Data Science
A data science degree can prepare you for data analytics, but it generally goes further into technical and mathematical subjects.
Data science programs may cover:
- Programming
- Statistics
- Machine learning
- Predictive modeling
- Artificial intelligence
- Data engineering
- Advanced analytics
This can make data science a good choice if you eventually want to work with predictive models or machine learning rather than primarily creating reports and dashboards.
The U.S. Bureau of Labor Statistics reports that data scientists typically need at least a bachelor’s degree in mathematics, statistics, computer science, or a related field. It projects 35% employment growth for data scientists from 2025 to 2035, much faster than the average for all occupations.
Best for: Students interested in advanced analytics, machine learning, predictive modeling, and technical data careers.
Program Learning Expectations for a Data Analytics Career
A good degree program for a career in data analysis should teach more than how to create charts.
You should expect some combination of statistics, databases, programming, data visualization, and applied problem-solving.
Statistics and Mathematics
Look for coursework in:
- Statistics
- Probability
- Regression
- Quantitative analysis
- Statistical modeling
These courses help you determine whether a pattern in a dataset is meaningful or simply the result of random variation.
Databases and SQL
SQL, or Structured Query Language, is used to retrieve and manipulate information stored in relational databases.
For example, a data analyst at an online retailer might use SQL to identify customers who purchased a particular product during the previous six months and then analyze their purchasing patterns.
SQL is not simply a resume keyword. It is a practical tool used in real analytics work. O*NET’s 2026 data for business intelligence analysts shows SQL as the most frequently mentioned software skill in its employer-posting data, followed by tools such as Power BI, Python, Tableau, and Excel.
Programming
Python and R are common programming languages in analytics.
You may use them to clean large datasets, automate repetitive tasks, perform statistical analysis, or create more advanced visualizations.
Not every entry-level data analyst needs extensive programming experience, but learning at least one programming language can broaden your career options.
Data Visualization
An analyst needs to communicate findings, not just calculate them.
Programs may teach visualization tools such as Tableau or Power BI and cover concepts such as:
- Choosing appropriate charts
- Building dashboards
- Identifying trends
- Presenting comparisons
- Communicating findings to nontechnical audiences
Business and Communication
A technically accurate analysis isn’t particularly useful if the people making decisions don’t understand it.
Business analytics and data analytics programs may therefore include courses that help students communicate findings through reports, presentations, dashboards, and recommendations..
Do You Need a Bachelor’s Degree to Become a Data Analyst?
Not every data analytics job has identical education requirements.
Some people enter analytics with certificates, associate degrees, data analytics job training, or experience in another profession. Others transition into analytics after earning a bachelor’s degree in a different field.
However, a bachelor’s degree can be a practical choice for someone starting from scratch, particularly when employers list a bachelor’s degree among their preferred qualifications.
It also gives you more time to develop a combination of technical and analytical skills through coursework, projects, internships, and electives.
If you’re already working in another field, you may not need to start over academically. Your existing experience could be relevant.
For example, someone with a finance background might move toward financial or business analytics. Someone with a marketing degree could pursue marketing analytics. A healthcare professional might use their industry knowledge as a foundation for healthcare analytics.
The key is to identify the skills required by the jobs you want and determine which ones you already have.
What Data Analysis Skills Should You Look for in a Degree Program?
When comparing programs, don’t focus only on the name of the degree.
Two colleges could both offer a “Bachelor’s in Data Analytics” while providing very different curricula.
Look for coursework that covers the following areas that will equip you with the necessary data analysis skills.
SQL and Database Management
Students should have opportunities to learn how data is stored and how to retrieve information from databases.
Statistics
Look for applied statistics, probability, regression, or statistical modeling.
Programming
Python or R can provide useful preparation for more advanced analytics.
Data Visualization
Look for hands-on experience with visualization and business intelligence tools.
Excel
Excel remains relevant for many business-oriented analytics roles, particularly when analysts are working with spreadsheets, financial information, or smaller datasets.
Real-World Projects
Projects can give you something tangible to discuss during an interview.
For example, a student might analyze public transportation data, build a dashboard showing changes in ridership, identify trends, and present recommendations based on the findings.
Communication
Look for assignments that require you to explain analytical results to people who don’t have a technical background.
This is an important distinction when comparing programs. An analyst’s job is rarely just “find the numbers.” The analyst often needs to explain what the numbers mean and what someone should do with them.
What Data Analyst Jobs Can You Get With a Bachelor’s Degree?
By choosing any one of the above suggested degrees could potentially can lead to a variety of roles depending on your skills and industry.
Potential job titles include:
- Data Analyst
- Business Analyst
- Business Intelligence Analyst
- Reporting Analyst
- Operations Analyst
- Marketing Analyst
- Financial Analyst
- Healthcare Data Analyst
- Business Intelligence Specialist
- Data Quality Analyst
The actual responsibilities can vary substantially even when two jobs have similar titles.
For example, a marketing analyst may spend much of the day examining campaign performance and customer behavior. An operations analyst might analyze supply chains, staffing, inventory, or production. A business intelligence analyst may spend more time building dashboards and reporting systems.
How to Choose the Best Degree for a Career in Data Analytics
There is no single best degree for everyone interested in data analytics.
Instead, match the degree to the type of work you want to perform.
Choose Data Analytics if:
You want the most direct academic path into data analysis and want coursework centered on analytics tools and methods.
Choose Business Analytics if:
You want to use data to solve problems involving marketing, finance, operations, management, or other business functions.
Choose Statistics if:
You enjoy mathematics and want a strong foundation in probability, statistical analysis, and quantitative methods.
Choose Computer Science if:
You enjoy programming and want the flexibility to move into technical areas such as data engineering, machine learning, or software development.
Choose Mathematics if:
You want a rigorous quantitative foundation and are comfortable adding applied statistics, programming, and data tools to your education.
Choose Information Systems if:
You want to understand databases, technology, and business processes alongside analytics.
Choose Data Science if:
You are interested in predictive modeling, machine learning, programming, and more advanced forms of analytics.
FAQs About Degrees for a Career in Data Analytics
What is the best major for becoming a data analyst?
Data analytics is one of the most direct majors, but it isn’t the only option. Business analytics, statistics, computer science, mathematics, information systems, and data science can also provide relevant preparation. When choosing a major, try to understand which degree program will best prepare for your chosen career path.
Is data analytics a good degree?
A data analytics degree can be a good choice if you want a curriculum specifically focused on analyzing data and using analytical tools to solve problems. Before choosing a program, review the curriculum to make sure it includes skills such as statistics, SQL, databases, data visualization, and programming.
Is a data analytics degree better than a computer science degree?
Neither is automatically better. Data analytics is generally more directly focused on analyzing data, while computer science provides broader and deeper preparation in programming and computing. Choose data analytics if you want a focused analytics curriculum; consider computer science if you want broader technical career options.
Is a statistics degree good for data analytics?
Yes. Statistics provides a strong foundation for understanding data, probability, statistical relationships, and analytical methods. You may need to supplement a statistics degree with SQL, programming, databases, and data visualization.
Can I become a data analyst with a business degree?
Yes. Business graduates can transition into analytics by developing technical skills such as SQL, Excel, data visualization, and statistics. A business background can be particularly useful for roles involving marketing, finance, operations, or business intelligence.
Is a master’s degree required to become a data analyst?
No. A master’s degree isn’t required for many data analyst positions. A bachelor’s degree can be sufficient for numerous entry-level and mid-level roles. Graduate education may become more useful if you want to specialize in statistics, data science, advanced analytics, or another quantitative field.
Start Your Search for a Data Analytics Degree
The best degree for a career in data analytics depends on the kind of analyst you want to become.
For many students, a data analytics degree or a degree in business analytics provides the most direct route. But statistics, computer science, mathematics, information technology or systems, and data science can each provide valuable preparation for different career paths.
When comparing programs, look beyond the degree title. Pay close attention to whether the curriculum teaches statistics, SQL, databases, programming, data visualization, and real-world analytical problem-solving. Those skills can help you move from learning about data to actually using it to answer questions and support decisions.
