Our Guide to the Best College and University Data Analytics Programs

That data is the core driver of business growth and innovation today is hardly news: for years we’ve been hearing about how data is the “new oil” of the 21st century. And fittingly, the numbers back this up. Data-savviness gives organizations a 3x better chance of making the right decision, at least according to a survey of top executives by PriceWaterhouseCoopers, as reported by Harvard Business School.

But even though the importance of data is established and the data analytics job market is booming — the US Bureau of Labor Statistics forecasts 23% growth by 2030, almost 5x the growth rate of the US job market as a whole — companies are struggling to cultivate data literacy among their employees. According to Gartner, a technological research and consulting firm, “[t]hrough 2025…the majority of CDOs will faiI to foster the necessary data literacy within the workforce to achieve their stated strategic data-driven business goals.” In other words, too few employees with data analytics skillsets means companies are leaving money on the table.

The good news? Increasingly, colleges and universities are providing educational opportunities for both future and current members of the workforce to get data-savvy through traditional bachelor’s and master’s programs and professional and executive education courses. Even better, there have never been more opportunities to study data analytics online, offering aspiring data-heads the flexibility to access quality education on their schedule, wherever they are.

With so many opportunities, however, choosing the right data analytics program can be difficult. In this guide, after we cover the basics of data analytics, we’ll dive into the different kinds of programs, including what they entail, who they’re for, and how much they cost. At the end, we’ll preview some of our favorites to get your research started if a university or college data analytics program seems like the right next step for you.

What is data analytics?

Before we dive into programs, let’s probe further into data analytics. We’ve already established how crucial data is for organizational decision-making — but how exactly is this data harnessed?

Data analytics is an interdisciplinary field that combines computer science, statistical analysis, and data management to derive intelligence and actionable insights from data. There are four primary kinds of data analytics — descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics — each with their own methods and focuses.

Descriptive analytics utilizes methods and techniques like data aggregation, data mining, and exploratory analysis to identify relationships, trends, and patterns in historical data. In essence, descriptive analytics answers the question, “what happened?”

Diagnostic analytics utilizes methods and techniques like drill-down, regression, data mining, and hypothesis testing to determine the causes of relationships, trends, and patterns that have been identified in historical data. If descriptive analytics seeks to answer the question, “what happened?,” diagnostic analytics instead seeks to answer the question, “why did something happen?”

Predictive analytics utilizes methods and techniques like decision trees, regression, clustering, and classification to develop models that can leverage data to predict future events. Often, this occurs with the help of machine learning. Rather than looking into the past, predictive analytics focuses on the question, “what might happen in the future?”

Prescriptive analytics utilizes methods and techniques like optimization, simulation, automation, and machine learning to determine the best courses of action for a business to take, answering the question, “what should we do in the future?”

For more on these types of analytics and examples of each, see our long-form explainer on data analytics.

In addition to the different types of data analytics, newcomers are often confused about how the overlapping fields of business analytics and data science distinguish themselves from data analytics. So how are these different?

What is business analytics?

In our minds, the distinction between the two business analytics and data analytics is one of emphasis, not essence: they share a set of skills, techniques, and tools, but business analytics emphasizes bigger picture business issues while data analytics focuses more on operations, products, or other discrete processes and initiatives.

For more on business analytics, see our full examination of the relationship between a data analyst and a business analyst, as well as our guide to business analytics master’s programs.

What is data science?

Another field that overlaps with data analytics is data science. But there is a crucial difference between the two: data science emphasizes the development of new techniques and tools to analyze big data sets (and so emphasizes artificial intelligence and machine learning), while data analytics usually relies on existing techniques and methods.

For more on data science, see our articles on:

Now that we’ve covered the core types of data analytics and explored the relationships between data analytics and the overlapping fields of business analytics and data science, we’ll dive into the core skills that data analytics requires.

What are the core data analytics skills?

Those working in data analytics require a core skillset comprising programming, statistical analysis, data management, and data visualization skills. For more advanced tasks in predictive and prescriptive analytics, advanced skills in areas like machine learning are also required.

Programming

Programming skills are required for data manipulation, advanced analysis, and data pipeline engineering. The most common languages for data analytics include Structured Query Language (SQL), used for database management; Python, a general-purpose language used for advanced analytics such as machine learning; and R, a programming language with specific application for statistics and data visualization.

Statistical analysis

Statistical analysis is the heart of data analytics: it’s what transforms data into actionable insights. As noted above, statistical techniques required vary depending on the kind of analytics in question. Common techniques include regression, optimization, clustering, and classification.

Data management

Successful analytics operations hinge on efficient and effective data management, from raw data collection, to storage, to preparation, to analysis.

Data visualization

Data analytics isn’t just about generating insights: communicating these insights to internal and external stakeholders is just as important. To do so effectively, data analytics professionals need to be able to create compelling data visualizations using tools like Tableau.

Machine learning skills

For advanced data analytics projects — and for advanced data analytics professionals — skill in machine learning, and even in deep learning, is essential.

While these skills can help professionals in a variety of positions — from marketing, to HR, to operations — better leverage data to improve performance, a data analytics skillset can also allow someone to take advantage of one of several lucrative career paths. We’ll get into these next.

What kinds of career paths are out there for someone with a data analytics skillset?

With programming, statistical analysis, data management, data visualization, and maybe even some machine learning skills, you can work in one of several data analytics roles: data analyst, business analyst, business intelligence analyst, and, in some cases, data scientist. As you’ll see, each of these roles offers an average salary well higher than $45,760, the US median annual wage in the US. So what do each of these roles entail?

Data analyst

A data analyst is responsible for collecting, preparing, and analyzing data to develop new insights to support the operations of their company. They communicate these insights to internal and external stakeholders through compelling data visualizations. According to Salary.com, in the US the average data analyst salary is $81,719.

Business analyst

A business analyst’s responsibilities are much the same as a data analyst’s — in fact, the two titles are often used interchangeably. If there’s a difference, as we noted above, it’s in a business analyst’s focus. Business analysts are also responsible for collecting, preparing, and analyzing data to extract insights, but more often they do so in support of larger business goals such as reducing costs, driving revenues, or entering a new market. According to Salary.com, in the US the average business analyst salary is $79,770.

Business intelligence analyst

A business intelligence analyst uses data and business analytics to produce informational support and dashboards monitoring KPIs and market and industry performance. According to Salary.com, in the US the average business intelligence analyst salary is $85,278.

Data scientist

A data analytics skillset, strong machine learning skills, and usually some work experience can allow you to land a data scientist job. Data scientists focus on devising, developing, and launching new approaches to data analysis. According to Salary.com, in the US the average data scientist salary is $139,631. If you’re interested in a data science path, you should also look into our guide to college and university data science programs.

So far, we’ve covered the components of a data analytics skillset and gone over what kinds of career paths this skillset can open up. In the next section, we’ll discuss how college and university data analytics programs can help.

How can college and university data analytics programs help you take the next step in your career?

While historically colleges and universities have offered bachelor’s and master’s degrees for those looking to gain on-the-job skills, increasingly these institutions of higher education (IHEs) are also offering professional education and executive education programs, both in person and online. Someone interested in learning data analytics at an IHE thus has never had more ways to do so. But how to know which kind of program is right for you? We’ll dive into the differences now.

Data Analytics Bachelor’s Degree Programs

What are they?

In the US, bachelor’s degrees are typically four-year undergraduate degrees during which students declare a major that determines their academic focus. While specific bachelor’s degrees in data analytics exist, oftentimes students interested in ultimately going into data analytics choose to major in related fields like applied mathematics, statistics, computer science, or even economics, finance, or business if they’re interested in business analytics. In addition to courses in their major, data analytics bachelor’s students take distribution courses in the social sciences and humanities as required by their institutions.

Who are they for?

Bachelor’s degrees are usually designed to be pursued right after high school, though students with nontraditional backgrounds are almost always welcome to apply. US bachelor’s degrees are also open to international students provided they can demonstrate English proficiency through a TOEFL or similar exam.

Young aspiring data analysts seek out bachelor’s programs because they offer broad, yet substantial training in both the theory and practice of data analytics and the chance to be exposed to a host of other interesting subject matter. They also do so because a bachelor’s degree from an accredited university is a strong credential that can support an entry-level job application. As we’ll see shortly, however, these programs are also for those who wish to make a significant financial investment in their future.

How much do they cost?

Tuition for bachelor’s programs varies widely depending on the reputation and location of the school, as well on whether it is a private or public college or university. According to educationdata.org, the average undergraduate paying in-state tuition at a public university pays a total of $102,828 over four years to attend (including books, fees, and housing), while an undergraduate at a private university pays $218,004 to attend for four years.

For more on data analytics bachelor’s programs, check out our guide. In the meantime, here are some of our favorites:

Carnegie Mellon’s Statistics Bachelor’s Degrees

A consistent leader in computational-based STEM, Carnegie Mellon’s Department of Statistics & Data Science offers several great majors for undergraduates interested in data analytics, including a Bachelor’s of Science in Statistics, a BS in Statistics and Machine Learning, and a BS in Economics and Statistics for someone interested in business analytics.

A highlight of Carnegie Mellon’s statistics BS programs is the Concentration Area, which allows students to choose four related courses from another field to complement their statistics study.

Program Highlights: “Reasoning with Data,” “Introduction to Statistical Research Methodology,” “Statistical Computing,” “Introduction to Machine Learning”

Program Length & Modality: 4 years, in person

Tuition: $62,260/year

New York University’s BS in Applied Data Analytics and Visualization

NYU’s BS in Applied Data Analytics and Visualization gives students the tools they need to analyze real-world data, extract insights, and communicate these insights compellingly. True to the major’s name, students are encouraged to apply their skills throughout the duration of their education through internships and an independent capstone project. Students in this major also complement their study of data with courses in literature, history, world culture, and writing.

Program Highlights: “Fundamentals of Computing,” “Database Design,” “Business Intelligence,” “Introduction to Cloud Computing”

Program Length & Modality: 4 years, in person

Tuition: $60,438/year

University of California – Berkeley’s BS in Data Science

Classified as “high-demand,” the data science major at UC Berkeley provides an interdisciplinary curriculum that can set undergraduates on a path to an entry-level data analytics or data science role. Students complete courses in math and data fundamentals, modeling and decision-making, ethics, and computation

Students also have the opportunity to take courses in a chosen domain emphasis, intended to provide context to their data analytics and data science studies. Potential emphases include: applied mathematics and modeling, business and industrial analytics, cognition, computational biology methods, data arts and the humanities, geospatial information and technology, and many others.

Program Highlights: “Principles and Techniques of Data Science,” “Data, Inference, and Decisions,” “Modern Statistical Prediction & Machine Learning,” “Beyond the Data: Humans and Values”

Program Length & Modality: 4 years, in person

Tuition: ~$14,500/year (in-state); ~$44,000/year (out-of-state)

Georgia Tech’s Bachelor’s of Science in Mathematics - Probability & Statistics

Georgia Tech’s BS in Mathematics - Probability & Statistics program offers a comprehensive education in the mathematics behind data analytics, plus introductory courses in computing, object-oriented programming, and machine learning that can help undergraduates build the data management and programming skills needed to put their math skills to work. Students also have the opportunity to complement their major courses with electives in the humanities, social sciences, and STEM.

Importantly, Georgia Tech offers this training for significantly less than most private and even many public universities, making the path to a data analytics career a possibility for all, regardless of financial situation.

Program Highlights: “Introduction to Computing for Data Analysis,” “Complex Analysis,” “Probability with Applications,” “Machine Learning”

Program Length & Modality: 4 years, in person

Tuition: ~$13,000/year (in-state); ~$34,000 (out-of-state)

Data Analytics Master’s Degree Programs

What are they?

A data analytics master’s degree is a graduate degree that provides advanced training in data analytics skills and concepts, often while giving students more freedom to pursue individual interests and projects than they would have as undergraduates.

Increasingly, data analytics master’s degrees are available online, following a broader trend in higher education: while just 5% of master’s students studied online in 2000 and 21% in 2012, in 2016 nearly a third of all master’s students did, according to Urban Institute. Given the successes and demand for remote learning since the onset of the coronavirus pandemic, quality online courses have continued to proliferate.

Who are they for?

Data analytics master’s degree programs are for bachelor’s degree holders — in STEM, in the social sciences, or even in the humanities — who are looking to either advance their existing analytics careers or transition into analytics careers.

How much do they cost?

Educationdata.org pegs the cost of the typical master’s of science degree in the US at $61,200, but the cost of the degree can range from $30,000 to $120,000 once fees are factored in. As with bachelor’s degrees, master’s degrees from public universities are significantly more affordable — averaging $29,150 — especially if a graduate student can take advantage of in-state tuition discounts. Studying online can bring additional savings if a student can forego relocation and commuting and continue working or taking care of familial obligations.

If you’re interested in learning more about the costs and benefits of a data analytics master’s degree, check out our deep dive on the topic. For more on what the degree entails, check out our guides on data analytics, business analytics (online MS programs), and analytics master’s. In the meantime, here are some of our favorite data analytics master’s programs:

The University of Chicago’s Master of Science in Analytics

The University of Chicago’s Master of Science in Analytics program offers students flexibility to study full-time or part-time, online or in person as they skill up with courses in advanced programming, data engineering architecture, machine learning, big data and cloud computing.

UChicago designed their MS in Analytics program for students with backgrounds in technical fields who have at least 2 years of work experience. With the part-time option, students are able to continue working full-time.

Students in the program can make use of a variety of career services, including career fairs, company info sessions, alumni networking events, and help with everything from resumes to interviewing. According to a quarterly survey administered by UChicago, 75% of students found a new job while completing the program.

Program Highlights: “Data Mining Principles,” “Statistical Analysis,” “Linear and Nonlinear Models for Business Application”

Program Length & Modality: 12-18 months (full-time); 18 months (part-time); online or in-person

Tuition: $62,556

Georgia Tech’s Master’s of Science in Analytics

Georgia Tech’s Master’s of Science in Analytics program offers foundational and advanced training in computing, statistics, operations research, and business along one of three tracks: analytical tools, business analytics, or computational data analysis.

Prior to enrolling, students of the program are expected to have demonstrated interest in data analytics, have a basic mathematics and computing background, and hold a bachelor’s degree. After taking core and elective courses, students have the opportunity to take an applied analytics practicum.

For students who are looking for a flexible alternative to Tech’s in-person program, there is a self-paced, online version of the MS Analytics degree offered.

Program Highlights: “Data Analytics in Business,” “Deep Learning,” “Data Science for Social Networks”

Program Length & Modality: 2 years (in-person); self-paced (online)

Tuition: $9,900

The University California – Berkeley’s Master of Analytics

Berkeley’s Master of Analytics program offers students training in core analytical methods and industry applications before placing them in a summer internship. Prior to beginning this compact 1-year master’s program, students take a Python bootcamp to build their programming skills.

Incoming students are expected to have existing training in linear algebra, probability, and statistics, and fluency in a computer programming language prior to applying will improve the quality of the application.

Program Highlights: “Risk Modeling & Simulation Analytics,” “Healthcare Analytics,” “Supply Chain Operations and Management”

Program Length & Modality: 1 year, in-person

Tuition: $66,700

Johns Hopkins’ Master of Science in Data Analytics and Policy

Many data analytics master’s programs are geared towards business application. This is particularly the case for business analytics master’s programs. Johns Hopkins’ Master of Science in Data Analytics and Policy program stands out by focusing squarely on how analytics can drive decision-making in policy areas like healthcare, the environment, criminal justice, education, and security.

Offered entirely online, students are able to pursue one of four concentrations — statistical analysis, geospatial analysis, public management, or political behavior and policy analysis — and complete their own capstone, all from the comfort of home. With a more fundamental curriculum than some other entries on the list, the program is perfect for students with backgrounds in the humanities and the social sciences who don’t have substantial computer science or statistics experience but want to improve their quantitative skills through graduate study to work in government, nonprofits, or think tanks.

Program Highlights: “Probability and Statistics,” “Machine Learning and Neural Networks,” “Financial Management and Analysis in Nonprofits”

Program Length & Modality: 16-24 months, online

Tuition: $55,260

Data Analytics Professional Education Programs

What are they?

College and university data analytics professional education programs offer shorter-term, targeted training in data analytics skills. These programs can take the form of a bootcamp, an intensive and comprehensive course of study that aims to place graduates in entry-level positions, or a certificate program, which generally covers similar material but is shorter, less intensive, and often more flexible.

Who are they for?

Professional education programs are a great option for professionals who want to improve their data analytics skills or even transition into the field but don’t want to invest the time and money required for a traditional two- or four-year degree program.

As most of these programs are online, they are great options for those who are already time-crunched or who want to learn from curricula designed by leading universities without traveling to them

How much do they cost?

The cost of college and university data analytics bootcamps and certificates vary widely depending on the length of the program, the modality, and the amount of career services offered. While some programs can be accessed for a small monthly fee through platforms like Coursera, others can cost upwards of $10,000.

For more on these kinds of programs, including those offered by organizations other than colleges and universities, check out our guides on data analytics courses, bootcamps, and certificates. In the meantime, here are some of our favorites:

Columbia Engineering Data Analytics Bootcamp

Columbia Engineering’s Data Analytics Bootcamp offers courses in Excel, Python, databases, and machine learning, as well as a final project that students are able to collaborate on with their peers. Throughout the bootcamp, students have access to academic and career support, including a Career Engagement Network that helps students prepare their resumes and portfolios and practice interviewing.

Program Highlights: “Excel crash course,” “Python data analytics,” “Machine learning and other advanced topics”

Program Length & Modality: 24 weeks, part-time online (9 hours of live classes per week, 20+ hours of homework per week)

Cost: $14,745

Georgetown University’s Data Analytics Bootcamp

Georgetown’s Data Analytics Bootcamp offers students the opportunity to learn data analysis and data visualization and apply these skills in collaborative projects. Georgetown also offers a course in critical thinking and 1:1 career services to help students find job placement after the course.

Program Highlights: “Foundations of Data Analytics & Python Basics,” “Statistics,” “Data Analytics in Python & SQL,” “Data Visualization”

Program Length & Modality: 12 weeks, Friday evenings and Saturdays, live online

Cost: $6,995

Berkeley Online Data Analytics Boot Camp

Cal Berkeley’s Data Analytics Boot Camp offers students the opportunity to practice skills like Excel, Python, API Interactions, and Machine Learning on projects focused around fields like finance, human resources, healthcare, and government. For those interested, Berkeley also offers a coding bootcamp.

Program Highlights: “Excel Crash Course,” “Python Data Analytics,” “Web Visualization”

Program Length & Modality: 24 weeks, with 9 hours of in-class time and 20+ hours of hands-on projects and practice work, live online

Cost: $9,995

Cornell’s Data Analytics Certificate Program

Cornell’s Data Analytics Certificate Program aims to give students who have a basic understanding of statistics a usable foundation in business analytics. Through three courses focused on data visualization, data-driven decision making, and predictive analytics, students learn to build dashboards that monitor key performance indicators (KPIs), develop incisive business questions, and create regression models that can predict the future.

Program Highlights: “Understanding and Visualizing Data,” “Implementing Scientific Decision Making,” “Using Predictive Data Analysis”

Program Length & Modality: 9 weeks (3 3-week courses), 3-5 hours per week, self-paced online

Cost: $2,625

Data Analytics Executive Education Programs

What are they?

Who are they for?

As most of these programs are online, they are great options for those who are already time-crunched or who want to learn from curricula designed by leading universities without traveling to them

How much do they cost?

For more on these kinds of programs, including those offered by organizations other than colleges and universities, check out our guides on data analytics courses, bootcamps, and certificates.

In the meantime, here are some of our favorites:

University of Chicago Booth’s Leading with Data and Analytics

UChicago Booth’s Leading with Data and Analytics program offers business leaders the opportunity to learn how to institute near- and long-term data-driven decision making solutions at their companies through the Chicago Booth Approach to analytics.

In addition to on-demand lectures, attendees interact with professors and each other in group learning and coaching sessions. Attendees also complete a final project.

Program Highlights: “Define your business objective,” “Articulate your theory,” “Construct your model,” “Generate insight”

Program Length & Modality: 30 hours of on-demand and live learning over 6 weeks, online

Tuition: $4,500-5,700

MIT Management Executive Education’s Data-Driven Teams: The Art and Science of Winning

MIT Management Executive Education’s Data-Driven Teams: The Art and Science of Winning program teaches executives how to leverage data to build powerful and efficient teams. Areas covered include talent identification, team organization, culture creation, and success assessment.

In addition to lessons and best practices from the sports world, this program features guest speakers from advertising, journalism, and data science. It can be taken online or on campus.

Program Highlights: “Why Teams Win,” “Data Workshop: Measuring your Team’s Talent,” “Designing and Implementing a Winning System”

Program Length & Modality: 2 days in person, 8 hours/day; 3 days live online, 4.5 hours/day

Tuition: $4,300

Columbia University’s Professional Certificate in Data Science for Executives

Columbia University’s Professional Certificate in Data Science for Executives, available on edX, offers a low-cost option for executives to gain background in the history, fundamental methods, and applications of data science, all at their own pace. Asynchronous courses taught by professors at Columbia’s Data Science institute focus in particular on data management and modeling, machine learning, and the Internet of Things (IoT).

Program Highlights: “Statistical Thinking for Data Science and Analytics,” “Machine Learning for Data Science and Analytics,” “Enabling Technologies for Data Science and Analytics: The Internet of Things”

Program Length & Modality: 4 months, self-paced online

Tuition: $297

What’s next?

We’ve covered a lot: the basics of data analytics, the kinds of programs that colleges and universities offer to help a broad swathe of individuals get data-savvy, and some of our favorites of these programs. If you’re interested in pursuing any of these courses, we’d recommend clicking the relevant links to head to the course pages to learn more. If you still want to know more about data analytics before doing so, check out the following articles: