What Can You Do with a Data Analytics Degree: 2025 Costs & Job Opportunities

Co-Founder and Chief Data Scientist

While data science is certainly a good choice for a future-proof career, choosing the right data analytics program can be a daunting task. Enrolling in the right data analytics degree ensures you gain the skills and expertise needed to adapt to market changes and growth, especially since the data analytics market is poised to grow from $7.03 billion in 2023 to $303.4 billion in 2030.

Drawing on my 10+ years of academic and career planning experience, I compiled essential information about a degree in the field. Read my guide to learn about its program length, costs, online offerings, requirements, and job opportunities.

What are the benefits of getting a degree in data analytics?

Employment opportunities for data analytics degree graduates are abundant in the finance and insurance, manufacturing, healthcare, and professional services industries.
A 2023 report shows that the median annual wage for data scientists is $103,500.
Online data analytics programs offer access to a global network of instructors and students.

What can I expect from a data analytics degree?

Data analytics degree programs allow students to forge careers in different industries, including manufacturing, media, and education.
A bachelor’s degree in data analytics can take four years to finish.
In public institutions, undergraduate programs in data analytics cost between $8,434 and $13,968 annually for resident students and between $13,666 and $16,238 annually for non-residents.
Common courses explore foundational mathematics and statistics, programming languages, data visualization, and machine learning.
Students are also expected to develop critical thinking and problem-solving skills, communication, and attention to detail.

Where can I work with a data analytics degree?

With a data analytics degree, you may choose from various career paths, including those of a data scientist, financial analyst, and economist.

Due to the spreading use of big data across various industries, you can also find employment in the following settings:

Finance
Insurance
Manufacturing
Healthcare
Professional services
Research and development
Social media
Sports
Entertainment

How much can I make with a data analytics degree?

The demand for individuals with knowledge and skills in data analytics results in higher-than-average salaries for data analytics graduates.

Data analysts can earn an annual income of $76,230.
The median annual wage for economists was $113,940.
Data scientists earned $103,500.
Financial analysts earned $96,220.

Best Data Analytics Programs for 2025
How long does it take to complete a data analytics program?
How does an online data analytics program compare to an on-campus program?
What is the average cost of a data analytics program?
What are the financial aid options for students enrolling in a data analytics program?
What are the prerequisites for enrolling in a data analytics program?
What courses are typically in a data analytics program?
What types of specializations are available in data analytics programs?
How to choose the best data analytics program?
Should I pursue an MBA to complement my data analytics skills?
What are employers looking for in data analytics graduates?
How can an accelerated computer science program complement your data analytics degree?
Can complementary certifications expand my career opportunities in data analytics?
How are data privacy and ethics addressed in data analytics programs?
Can integrating artificial intelligence elevate your data analytics career?
How can interdisciplinary programs complement a data analytics degree?
What career paths are available for graduates of data analytics programs?
What is the job market for graduates of a data analytics program?
How important are programming skills in a data analytics degree?
What are the differences between data analytics and data science programs?
How does a data analytics degree prepare you for a career in emerging fields?
Other Things You Should Know About Data Analytics Programs

Best Data Analytics Programs for 2025

How do we rank schools?

I used datasets from the IPEDS database, Peterson’s database, the College Scorecard database, and the National Center for Education Statistics (NCES) to gather the best degree programs in data analytics. I understand that paying for a degree is an important investment, so my team and I deployed a methodology relying only on comprehensive and transparent information to help students make an informed decision for their education.

1. Bentley University BS in Data Analytics

Bentley University‘s hybrid data analytics program is a combination of mathematics, statistics, and computing subjects. It also offers hands-on training in Python, R, and SQL.
Students are required to take classes in calculus, statistics, and data mining, while additional electives in mathematics and business allow students to explore areas of interest.

Program Length: 4 years
Estimated Cost: $58,150
Required Credits to Graduate: 122
Accreditation: New England Commission on Higher Education (NECHE)

2. Bryan College-Dayton BS in Data Analytics

Bryan College-Dayton offers an on-campus BS in Data Analytics focusing on math, programming, and research. The major combines courses in computer science and statistics, while allowing students to pursue electives and gain in-depth knowledge in related areas such as psychology, finance, or business.

Program Length: 4 years
Cost per Credit: $395
Required Credits to Graduate: 120
Accreditation: Southern Association of Colleges and Schools Commission on Colleges (SACSCC)

3. CUNY New York City College of Technology BS in Data Analytics/Economics

This dual data analytics and economics program from New York City College of Technology prepares students for entry-level roles across occupations, which include healthcare, finance, and public policy, to name a few. This traditional degree requires fulfilling a research project or participating in a semester-long internship.

Program Length: 4 years
Cost per Credit: $305 (resident); $620 (non-resident)
Required Credits to Graduate: 120
Accreditation: Middle States Commission on Higher Education

4. Drake University BS in Data Analytics

Drake University, in partnership with Zimpleman College of Business, is delivering an online + in-person BS in Data Analytics program. Students have the option to pursue this degree as a major for the Bachelor of Science in Business Administration degree in the Zimpleman College of Business, where data analytics is explored in the context of finance, marketing, or other fields of business. A data analytics major is also available through Drake University’s College of Arts and Sciences. This major is built on a foundation of computer science and statistics.

Program Length: 4 years
Cost Per Semester: $24,733
Required Credits to Graduate: 120
Accreditation: Higher Learning Commission (HLC)

5. Lynn University BS in Data Analytics

Lynn University‘s traditional BS in Data Analytics offering combines IT, math, and business to help graduates enter the IT industry. Its focus is on data mining, programming, and visualization.

Program Length: 4 years
Tuition: $41,200/year
Required Credits to Graduate: 120
Accreditation: SACSCC

6. University of Illinois at Urbana-Champaign Master of Computer Science in Data Science

University of Illinois at Urbana-Champaign offers a 100% online master’s program in data science, equipping students with expertise in machine learning and cloud computing, among others. It also teaches skills in statistics and information science.

Program Length: No information available
Cost Per Credit: $686
Required Credits: 32
Accreditation: HLC

7. University of Wisconsin MS in Data Science

This data science graduate degree offered by University of Wisconsin is a joint program between the university’s Statistics and Computer Sciences Department. This hybrid program’s coursework includes statistical theories and methodologies, computer systems and algorithms, machine learning, and some electives.

Program Length: No information available
Cost Per Credit: $1,600
Required Credits:30
Accreditation: HLC

8. John Hopkins Engineering for Professionals MS in Data Science

Johns Hopkins University is constantly ranked as one of the top schools in the country. IWith no GRE requirement, this master’s program offers courses in computer science and applied mathematics. Students also have the option to pursue a master’s degree or a post-master’s certificate.

Program Length: No information available
Cost Per Credit: $2,013
Required Credits: 30
Accreditation: Middle States Commission on Higher Education

9. Colorado State University PhD in Systems Engineering

Colorado State University offers an online PhD in Systems Engineering to help with today’s complex problems. It teaches engineers to utilize tools from different fields, such as control systems, operations research, software engineering, and networking and security.

Program Length: Varies based on intensity of study and previous coursework
Cost Per Credit: $1,152
Required Credits: 72
Accreditation: HLC

10. University of Virginia PhD in Data Science

University of Virginia designed this doctorate degree in data science for the next generation of data science specialists. Its ultimate goal is to retrieve knowledge and discover complex data through vigorous applied training.

Program Length: 5-6 years
Tuition: starts at $15,786
Required Credits: No information available
Accreditation: SACSCC

Here’s what graduates have to say about their data analytics degrees

Studying data analytics online opened up a world of flexibility and real-world application. The hands-on projects and case studies not only honed my technical skills but also gave me the confidence to tackle complex problems in the industry. Being able to balance coursework with my professional life was a game-changer, making the online learning experience truly transformative. Thanks to this program, I now thrive as a data analyst, turning raw data into actionable insights every day. Raul

The online data analytics program provided an invaluable mix of theoretical knowledge and practical skills. Collaborating with classmates from diverse backgrounds on virtual projects mirrored the real-world teamwork I encounter in my data science role today. The constant interaction with industry professionals during webinars and virtual networking events gave me a head start in building a robust professional network. Studying online didn’t just fit my schedule; it brought the industry into my living room, making my learning journey both enriching and rewarding. Mei

Embarking on an online data analytics degree was a transformative journey that blended the convenience of remote learning with the rigors of a top-notch curriculum. The program’s emphasis on real-world applications allowed me to seamlessly transition from the virtual classroom to my current role as a data engineer. The continuous mentorship from experienced online instructors and access to cutting-edge tools equipped me with the skills needed in today’s fast-paced data landscape. Studying online not only accommodated my work commitments but also instilled in me a sense of self-discipline and adaptability crucial in the evolving field of data analytics. Aisha

Key Findings

The minimum required SAT score for college admission is between 1160 and 2300, while the minimum ACT score is 25.
84.4% of recruiters look at applicants’ machine learning skills during the hiring process.
Some schools offering data analytics degrees have a student-to-teacher ratio of around 17:1.
Employment for data scientists is expected to increase by 35% between 2022 and 2032.
The Computer Systems Design and Related Services industry employed the most number of data scientists, 21,440, last year.

How long does it take to complete a data analytics program?

An associate’s degree in data analytics generally takes two years to complete. Earning this degree may be a springboard toward a bachelor’s degree in data analytics, computer science, or other related fields. That said, a bachelor’s degree in data analytics spans four years, which provides more complex technical training and coursework.

Many professionals in the field strive for career progress, and earning a master’s degree and/or a doctoral degree in data analytics may be a good option for them. These degrees can be earned in four to five years.

Considering the courses and specializations in data analytics, it can be said that it is a common ground for business and information technology, which is also related to engineering. Of the 2.1 million bachelor’s programs conferred in the US in 2021, business and engineering were the most common degrees granted.

How does an online data analytics program compare to an on-campus program?

Online programs allow students to study at their convenience and often cater to working professionals. These programs typically leverage digital platforms, offering access to a global network of instructors and students.

On the other hand, on-campus programs provide a traditional classroom experience. This setting can be conducive to prompt feedback, in-person collaboration, and networking opportunities. On-campus learning also provides access to physical resources such as laboratories and libraries.

The content and curriculum of online and on-campus data analytics programs can be quite similar. Their only difference is the mode of delivery and the level of interaction with instructors and peers.

What is the average cost of a data analytics program?

Private academic institutions offering online associate’s degrees in the discipline charge students an estimated $9,600 to $14,820 per year. Meanwhile, on-campus alternatives offered by private universities cost about $11,970 per year. Public universities cost the least, at an estimated $6,840 to $8,550 per year.

For a bachelor’s degree in data analytics, private academic institutions offer it online for about $9,637 to $15,454.8 per year and on campus for an estimated $16,500 to $54,980 per year. Public universities offer the in-person option between $8,434 and $13,968 per year for in-state students and between $13,666 and $16,238 per year for out-of-state students.

For master’s and doctorate degrees, private universities offer them online and on-campus at an estimated $62,556 for the entire program. In contrast, public academic institutions charge an estimated $32,060 to $36,000 for the entire program for in-state students and an estimated $32,060 to $39,000 for the entire program for out-of-state students.

What are the financial aid options for students enrolling in a data analytics program?

For financial aid options, check out the Acxiom Diversity Scholarship, Milliman Opportunity Scholarship Fund, AIGC Science Post-Graduate Scholarship, and ASA Pride Scholarship.

Acxiom Diversity Scholarship. This scholarship grants funds for bachelor’s and graduate students taking data science. It prioritizes students in underrepresented groups, choosing up to 10 candidates.
Milliman Opportunity Scholarship Fund. This one funds present or future bachelor’s students in data science, actuarial science, and statistics. It is administered by Scholarship America and grants 15 to 25 scholarships every year.
AIGC Science Post-Graduate Scholarship. It grants funds for training opportunities in science and mathematics fields. Its total amount ranges from $1,200-$10,000.
ASA Pride Scholarship. Offered by the American Statistical Association (ASA), this scholarship raises awareness and supports LGBTQIA+ data scientists, statisticians, and allies. Candidates must be enrolled in a data science or statistics graduate program or have acquired their degree within five years of the award date.

What are the prerequisites for enrolling in a data analytics program?

To give yourself a better chance and beat application deadlines, ensure that you obtain these documents and develop the following skills:

Admission Requirements

Proof of Graduation. To be able to officially move up to college, you must be able to present proof that you are a high school graduate. This includes a high school diploma, a general education development (GED) transcript, or a certificate of completion.
Transcripts. Your transcript of records provides admissions officers with a summary of your academic performance. This helps them determine if you are qualified to be accepted into the program, as past records may indicate future performance.
SAT or ACT score. Academic institutions may require you to submit your SAT or ACT scores. The minimum required SAT score for admission is between 1160 and 2300, while the minimum ACT score is 25.
Other requirements. Some institutions include essays or letters of recommendation in their application requirements. These requirements give admissions officers a glimpse into your personality, self-awareness, and ability to express yourself. They also help vouch for your skills and academic performance.

Skill Requirements

Presentation Skills. The presentation of insights by data analysts to their audience is just as important as the task of data analysis itself. Effective analysis and presentation may guide organizations in informed decision-making, potentially resulting in the maximized use of resources, streamlined operations, and enhanced products and services.
Rational-thinking Skills. Rational thinking benefits problem-solving tasks as it helps an individual use logical reasoning and weed out irrelevant details. Then, it enables the individual to produce conclusions or solutions based on evidence.
Computer Literacy. Colleges offering data analytics degrees go to lengths to ensure their students are equipped with the tools, methods, and software needed to become effective professionals after graduation. On the students’ part, they first need to have enough technological know-how to pass admissions.

What courses are typically in a data analytics program?

As an academic discipline, a data analytics degree may include the following courses:

Introduction to Data Analytics. This foundational course provides an overview of key data analytics concepts, methodologies, and tools. Students gain an understanding of the role of data analytics in decision-making and problem-solving across various industries.
Statistics and Probability. Focusing on fundamental statistical principles, this course equips students with the skills to analyze and interpret data. Topics include probability distributions, hypothesis testing, and regression analysis.
Programming for Data Analysis. This course introduces students to programming languages such as Python or R, emphasizing data manipulation, analysis, and visualization. Students develop coding skills to extract valuable insights from datasets and automate analytical processes.
Database Management and SQL. Covering database fundamentals and Structured Query Language (SQL), this course tea ches students to design and manage databases. Students learn how to query databases to retrieve, modify, and analyze data efficiently.

What types of specializations are available in data analytics programs?

Specializations such as business analytics, healthcare analytics, big data analytics, and financial analytics, give a deeper understanding of how data analytics can be applied in various contexts. I explained each specialization below to help you decide if this degree, among other information technology degrees, is a good choice for you.

Business Analytics. The Business Analytics specialization delves into leveraging data to make informed business decisions. Students explore predictive modeling, data-driven strategy, and business intelligence.
Healthcare Analytics. Focused on the healthcare industry, this specialization teaches students to analyze and interpret medical data to improve patient care, streamline operations, and optimize healthcare systems. Students gain skills in healthcare data management, predictive analytics, and the application of data-driven solutions in medical settings.
Big Data Analytics. The Big Data Analytics specialization concentrates on handling and analyzing massive datasets using advanced technologies. Students gain expertise in processing and deriving insights from large-scale and complex data structures.
Financial Analytics. The Financial Analytics specialization applies data analysis techniques to financial data, supporting decision-making in areas, such as investment, risk management, and financial forecasting. Students acquire skills in financial modeling, algorithmic trading, and evaluating economic trends using data.

How to choose the best data analytics program?

The criteria when choosing the best data analytics program include accreditation and reputation, flexibility, student-to-teacher ratio, and alumni network. Because working through any college degree type is a major commitment, taking your time with it is reasonable.

Accreditation and Reputation. Look for programs offered by accredited institutions with a strong reputation in data analytics. Accreditation ensures that the program meets certain quality standards, and a positive reputation indicates recognition by industry professionals.
Flexibility (Online vs. On-Campus). Consider your preferred learning environment. An online program might be suitable if you need flexibility due to work or other commitments. On the other hand, if you value in-person interactions, an on-campus program may be more appealing.
Student-to-teacher Ratio. Over the years, studies have found that large class sizes may pose challenges to educational outcomes for students. Fortunately, some U.S. academic institutions offering data analytics degrees have a relatively low student-to-teacher ratio of around 17:1.
Alumni Network. Explore the program’s alumni network and their achievements. A strong alumni network can provide valuable networking opportunities, mentorship, and insights into potential career paths.

Should I pursue an MBA to complement my data analytics skills?

Supplementing technical expertise with advanced business knowledge can strategically position graduates for leadership roles. Pursuing an MBA provides a comprehensive understanding of management, strategy, and operations that directly enhances one’s ability to drive data-informed decision-making in complex organizational settings. This additional credential helps bridge the gap between analytics and executive management, offering a competitive edge in efficiently communicating insights to stakeholders and shaping business strategy. For a cost-effective solution that integrates business leadership with technical analytics, consider an affordable online MBA in data analytics.

What are employers looking for in data analytics graduates?

Employers in the data analytics field prioritize a blend of technical expertise and strategic thinking. Decision-makers seek professionals who can not only manipulate large datasets but also effectively communicate insights and drive business outcomes. Demonstrated abilities in data visualization, problem-solving, and cross-functional collaboration are highly valued. Additionally, real-world project experience that showcases an aptitude for applying theoretical knowledge to practical challenges is a key differentiator. Some candidates further bolster their profiles by pursuing complementary qualifications, such as online masters in biotechnology, which can enhance interdisciplinary perspectives and broaden career opportunities.

How can an accelerated computer science program complement your data analytics degree?

Integrating specialized computer science skills can bridge gaps between analytical theory and practical application. Exposure to an accelerated curriculum, such as a computer science accelerated program, provides focused training in algorithm development, system design, and advanced programming techniques that are directly applicable to data processing challenges. This combined approach enhances problem-solving capabilities and supports the swift adoption of emerging technologies in data analytics.

Can complementary certifications expand my career opportunities in data analytics?

Advanced roles in data analytics often require skills that extend beyond core technical expertise. Supplementary certifications can provide a competitive edge by demonstrating proficiency in complementary areas such as cybersecurity, risk management, or specialized data platforms. For example, integrating cybersecurity knowledge can enhance your ability to safeguard sensitive information and support robust data governance solutions. Pursuing an affordable online cyber security degree is a practical option to build expertise that directly benefits data protection strategies and cross-functional collaboration in today's data-driven workplaces.

How are data privacy and ethics addressed in data analytics programs?

Data analytics curricula are increasingly incorporating comprehensive modules on data privacy, ethical decision-making, and regulatory compliance to equip graduates with the skills necessary for responsible data handling. These programs emphasize frameworks for assessing bias, safeguarding sensitive information, and maintaining transparency in reporting insights. Integrating case studies and real-world scenarios, they foster a clear understanding of the implications associated with data misuse and promote innovative, cross-disciplinary problem-solving. This approach not only reinforces technical prowess but also prepares professionals to engage confidently with complex legal and societal challenges while exploring complementary disciplines, such as cheap online masters in architecture degree, that further enhance creative analytical perspectives.

Can integrating artificial intelligence elevate your data analytics career?

Integrating artificial intelligence (AI) into data analytics can offer a decisive competitive edge by enhancing data modeling and expanding predictive capabilities. Advanced AI techniques streamline complex data processes and foster innovative problem-solving approaches that redefine traditional analytics. For professionals aiming to diversify their technical expertise and secure leadership roles in tech-driven industries, acquiring AI competencies can be transformative. In this context, supplementing your data analytics skill set with a fastest master's degree in artificial intelligence online can provide a strategic advantage, enabling you to stay at the forefront of emerging trends while driving measurable business impact.

How can interdisciplinary programs complement a data analytics degree?

By integrating expertise from diverse fields, data analytics programs can offer graduates a competitive edge in addressing industry-specific challenges. Combining technical data skills with specialized knowledge broadens career options and enhances the ability to derive insights in niche areas. For example, supplementing your studies with an online bioinformatics masters degree can foster a deeper understanding of biological data interpretation, enabling innovative approaches within healthcare, research, and biotechnology sectors. This interdisciplinary approach not only refines analytical methods but also equips professionals to lead complex projects that require both a robust technical foundation and subject-specific acumen.

What career paths are available for graduates of data analytics programs?

Data science, economics, and financial analysis are some common career paths for data analytics graduates.

Data Scientist. Data scientists create algorithms—procedures to solve problems in computer programming—to gather and analyze large quantities of data. Effective algorithms can identify information or trends that humans fail to see. Not to mention, they can do so much faster than humans. Data science can help organizations generate customer or market insights, boost data security, and detect their financial health.
Economist. Economists use data to study large-scale economics—say, the financial state of a country—and small-scale economics—for instance, family wealth. Their data analysis helps spot patterns and issues in entities to inform their preventive and restorative measures and maintain financial stability.
Financial Analyst. Financial analysts collect, organize, and analyze data to forecast an organization’s performance. They also provide recommendations to enhance an entity’s operations, reduce costs, and increase revenue, among other areas for growth.

What is the job market for graduates of data analytics programs?

As the world continues to generate a vast amount of data, more data analysts are in demand than ever. Employment for data scientists, who often start their careers as data analysts, is expected to increase by 35% between 2022 and 2032, according to the 2023 data from the United States Bureau of Labor Statistics (BLS).

Various sectors in different industries are also taking advantage of this information explosion by opening and filling many data analytics degree jobs and related professions. The same BLS data shows that the Computer Systems Design and Related Services industry employed 21,440 data scientists last year. Other industries with the highest levels of employment in data scientists are shown in the chart below.

How important are programming skills in a data analytics degree?

Programming skills are fundamental to success in data analytics. A strong understanding of programming languages is crucial for data manipulation, automation, and analysis. Here’s why programming is so important in a data analytics degree:

Data Manipulation and Cleaning: Programming languages like Python and R allow data analysts to clean, transform, and organize large datasets, preparing them for analysis. Without programming, this process would be tedious and error-prone.
Automation of Repetitive Tasks: Programming helps automate repetitive tasks, saving time and ensuring consistency. Analysts can quickly process vast amounts of data using scripts, making the workflow more efficient.
Advanced Data Analysis: With programming knowledge, students can conduct more advanced analyses such as machine learning, predictive modeling, and statistical testing. These techniques are essential for gaining deeper insights from data.
Database Management: SQL is a critical language for querying databases and retrieving relevant data. A solid understanding of SQL allows data analysts to access and manipulate large datasets stored in databases.
Visualization Tools Integration: Programming also integrates data with visualization tools like Tableau or Power BI. Analysts often need to write code to pull data from various sources and prepare it for easy-to-understand visual representations.

What are the differences between data analytics and data science programs?

While data analytics and data science programs share similarities, they also have distinct differences that can impact your career path. It's important to understand these differences when deciding which program to pursue, as they align with different skill sets and career opportunities. Here’s an overview of what you should know:

Focus on Data: Data analytics programs primarily focus on interpreting and analyzing existing data to help businesses make informed decisions. In contrast, data science programs delve into building algorithms, predictive models, and advanced statistical techniques to explore complex data and uncover hidden insights.
Skill Development: In data analytics programs, students often learn tools like Excel, SQL, and Tableau, focusing on visualizing and analyzing data trends. Data science programs, however, typically include advanced programming languages such as Python, R, and machine learning frameworks, providing a deeper dive into coding and data manipulation.
Career Opportunities: Graduates from data analytics programs typically work in roles like data analysts or business intelligence analysts, focusing on operational efficiency and reporting. Data science graduates, however, often take on roles such as data scientists, machine learning engineers, or research scientists, working on more technical and innovative projects.
Program Length and Depth: While both programs can be pursued at the undergraduate or master's level, data science programs, especially at the cheapest online data science masters level, tend to be more advanced and in-depth, requiring more years of study and a stronger foundation in math, programming, and statistics.
Data Tools and Techniques: In data analytics, the focus is often on using ready-made tools and methods to analyze data, while data science involves creating custom algorithms and models, which requires a higher level of technical expertise.

How does a data analytics degree prepare you for a career in emerging fields?

The ever-evolving landscape of technology and data has opened doors to numerous emerging career opportunities for data analytics graduates. A data analytics degree not only provides the technical expertise needed to excel in traditional roles but also prepares students to adapt and thrive in fields shaped by innovation. Here’s how this degree equips graduates for emerging career paths:

Artificial Intelligence and Machine Learning: Students gain foundational knowledge in data processing, statistical modeling, and programming languages like Python and R, which are critical for AI and machine learning roles. This knowledge enables graduates to build algorithms and analyze large datasets for AI-driven applications.
Healthcare Analytics: With the growing importance of data in healthcare, students learn to interpret medical data to improve patient outcomes, optimize operations, and support precision medicine initiatives. Skills in predictive analytics and data visualization are particularly valuable in this sector.
Sustainability and Environmental Data: As organizations prioritize sustainability, data analysts are needed to measure environmental impact, track carbon footprints, and optimize resource utilization. Graduates with expertise in big data can help drive eco-friendly business strategies.
E-commerce and Personalization: Data analytics students develop skills in consumer behavior analysis, enabling them to create personalized shopping experiences. This is particularly relevant as e-commerce platforms rely on predictive models to enhance user engagement.
Cybersecurity Analytics: The intersection of data analytics and cybersecurity is a rapidly growing field. Analysts use their skills to detect anomalies, assess risks, and develop strategies to protect sensitive information from breaches.

For those exploring career paths that leverage data expertise, learning about how to become a data scientist offers further insights into related roles requiring advanced analytical skills.

By equipping students with versatile, in-demand skills, a data analytics degree empowers graduates to navigate and excel in these dynamic, high-growth fields.

Other Things You Should Know About Data Analytics Programs

What is an example of data analytics?

One example of data analytics is customer segmentation in marketing. Companies collect and analyze customer data, such as purchasing history, demographics, and online behavior, to categorize customers into distinct segments. By identifying common characteristics within each segment, businesses can tailor marketing strategies to target specific groups more effectively.

A retailer, for example, might use data analytics to recognize high-value customers, understand their preferences, and create personalized promotions to enhance customer loyalty.

What are the four main types of data analytics?

The four main types of data analytics are descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Descriptive analytics involves examining historical data to provide insights into what has happened in the past, typically through summary statistics, charts, and graphs. Diagnostic analytics goes a step further by understanding why certain events occurred and identifying patterns and correlations in the data.

Predictive analytics utilizes statistical algorithms and machine learning models to forecast future trends and outcomes based on historical data. Finally, prescriptive analytics offers actionable recommendations by suggesting optimal courses of action to achieve desired outcomes, often leveraging insights from predictive analytics.

High demand and job security: Data analysts are in high demand across various industries. This translates to ample job opportunities and excellent career prospects.
Lucrative salaries: Data analysts earn competitive salaries. This attractive salary potential makes data analytics a rewarding career choice.
Transferable skills: The skills you learn in data analytics, like data analysis, visualization, and problem-solving, are valuable across various sectors. This versatility allows you to explore different career paths within data analysis or move to other fields, providing greater career flexibility.
Intellectual challenge and growth: Data analysis is a dynamic and constantly evolving field. You’ll constantly learn new tools, techniques, and knowledge, keeping your work intellectually stimulating and rewarding.

Still, whether a data analytics degree is worth is largely dependent on your career goals, financial situation, and your technical skills.

What types of data analysis tools are used in the data analytics program?

In the data analytics program, students delve into the world of data analysis, gaining skills vital for today's data-driven industries. Here's a glimpse into the software and tools commonly utilized:

Python: A versatile programming language for data analysis and manipulation.
R: Widely used for statistical analysis and data visualization.
SQL: Essential for managing and querying databases.
Tableau: Enables interactive data visualization and dashboard creation.
Excel: Fundamental for basic data manipulation and analysis.
SAS: Utilized for advanced statistical analysis and predictive modeling.

How does a background in mathematics or statistics benefit future data analysts?

A background in mathematics or statistics is invaluable for a data analyst. It provides the foundation for understanding data patterns, creating predictive models, and making data-driven decisions. Statistical knowledge helps in designing experiments, analyzing trends, and ensuring the accuracy of results. Mathematical skills, such as linear algebra and calculus, are essential for developing complex algorithms and data transformation processes. Overall, this background empowers a data analyst to extract meaningful insights, identify correlations, and communicate findings effectively, contributing significantly to informed business strategies and decision-making processes.

What kind of real-world projects and practical applications are included in a data analytics degree?

A data analytics degree program includes real-world projects and practical applications to ensure students gain hands-on experience. These projects often involve analyzing large datasets, developing predictive models, and using data visualization tools to uncover insights. Students work on case studies from various industries, participate in internships, and collaborate with companies on data-driven projects. They also use industry-standard software and programming languages such as Python, R, and SQL. This practical approach helps students develop critical thinking and problem-solving skills, preparing them to tackle real-world data challenges and make informed business decisions in their future careers.

References:

Arizona State University. Business Data Analytics. ASU.
CFI Team. (2022, December 4). What does a financial analyst do. Corporate Finance Institute.
Ohio State University. (n.d.). Specializations in the major. Data Analytics Major. OSU.
Salesforce. (2023, November 9). Salesforce launches global digital skills index: In-depth insights from 23,000 workers. Salesforce.
U.S. Bureau of Labor Statistics. (n.d.). Data scientists. BLS.
Wang, L., & Calvano, L. (2022). Class size, student behaviors and educational outcomes. Organization Management Journal, 19(4), 126-142. DOI.