Master’s in Data Analytics Online

<a href="https://www.onlinemasterscolleges.com/masters-in-data-analytics-online/">Data Analytics Online</a>

College Name & Address	Tuition	Graduation Rate
#1 Georgia Institute of Technology 225 North Ave, Atlanta, Georgia 30332	$14,064	90%
#2 Villanova University 800 Lancaster Avenue, Villanova, Pennsylvania 19085	$20,619	90%
#3 University of Wisconsin Madison 500 Lincoln Dr, Madison, Wisconsin 53706	$10,728	88%
#4 Worcester Polytechnic Institute 100 Institute Road, Worcester, Massachusetts 01609	$28,980	89%
#5 Texas A&M University JKW Administration Building, Suite 200, College Station, Texas 77843	$6,775	82%
#6 Saint Louis University One North Grand Blvd, Saint Louis, Missouri 63103	$21,420	79%
#7 American University 4400 Massachusetts Ave NW, Washington, District of Columbia 20016	$34,533	79%
#8 Colorado State University, Global Campus 585 Salida Way, Aurora, Colorado 80011	$9,000	NA
#9 Brandeis University 415 South St, Waltham, Massachusetts 02454	$51,940	87%
#10 Boston University One Silber Way, Boston, Massachusetts 02215	$56,854	88%
#11 University of Missouri 105 Jesse Hall, Columbia, Missouri 65211	$9,478	71%
#12 George Mason University 4400 University Dr, Fairfax, Virginia 22030	$12,594	71%
#13 Oregon State University 1500 SW Jefferson Avenue, Corvallis, Oregon 97331	$13,257	67%
#14 New Jersey Institute of Technology University Heights, Newark, New Jersey 07102	$20,624	67%
#15 University of North Texas 1501 W.Chestnut Ave., Denton, Texas 76203	$6,350	56%
#16 Southern New Hampshire University 2500 North River Road, Manchester, New Hampshire 03106	$18,810	44%
#17 Harrisburg University 326 Market Street, Harrisburg, Pennsylvania 17101	$7,200	31%
#18 Western Governors University 4001 South 700 East Suite 700, Salt Lake City, Utah 84107	$7,500	21%
#19 University of Maryland Global Campus 3501 University Blvd East, Adelphi, Maryland 20783	$8,640	15%

Source – Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available

<a href="https://www.onlinemasterscolleges.com/masters-in-data-analytics-online/">Data Analytics Online</a>

College Name & Address	Tuition	Graduation Rate
#1 Dakota State University 820 N Washington Ave, Madison, South Dakota 57042	$5,939	43%
#2 University of North Texas 1501 W.Chestnut Ave., Denton, Texas 76203	$6,350	56%
#3 Emporia State University 1 Kellogg Circle, Emporia, Kansas 66801	$6,547	50%
#4 Texas A&M University JKW Administration Building, Suite 200, College Station, Texas 77843	$6,775	82%
#5 University of Oklahoma 660 Parrington Oval, Norman, Oklahoma 73019	$6,943	70%
#6 Harrisburg University 326 Market Street, Harrisburg, Pennsylvania 17101	$7,200	31%
#7 Western Governors University 4001 South 700 East Suite 700, Salt Lake City, Utah 84107	$7,500	21%
#8 University of Illinois Springfield One University Plaza, Springfield, Illinois 62703	$8,247	54%
#9 University of Maryland Global Campus 3501 University Blvd East, Adelphi, Maryland 20783	$8,640	15%
#10 Colorado State University, Global Campus 585 Salida Way, Aurora, Colorado 80011	$9,000	NA
#11 University of Missouri 105 Jesse Hall, Columbia, Missouri 65211	$9,478	71%
#12 University of Wisconsin Madison 500 Lincoln Dr, Madison, Wisconsin 53706	$10,728	88%
#13 University of California, Los Angeles 405 Hilgard Ave, Los Angeles, California 90095	$11,442	92%
#14 George Mason University 4400 University Dr, Fairfax, Virginia 22030	$12,594	71%
#15 Oregon State University 1500 SW Jefferson Avenue, Corvallis, Oregon 97331	$13,257	67%
#16 Saint Joseph’s University 5600 City Avenue, Philadelphia, Pennsylvania 19131	$17,802	81%
#17 Southern New Hampshire University 2500 North River Road, Manchester, New Hampshire 03106	$18,810	44%
#18 Villanova University 800 Lancaster Avenue, Villanova, Pennsylvania 19085	$20,619	90%
#19 Saint Louis University One North Grand Blvd, Saint Louis, Missouri 63103	$21,420	79%

Source – Integrated Post Secondary Education Data System & University Data
*Tuition rates are for in-state and per year. Program specific rates may apply.
**NA – data not available

Master’s in Data Analytics programs include advanced statistical analysis, machine learning, and data visualization coursework. Students develop expertise in handling large datasets, utilizing programming languages like Python or R, and applying statistical models to extract valuable insights. The curriculum often includes real-world projects, and sharpening practical skills. Graduates are equipped to navigate the complexities of data analytics, making informed decisions and contributing to innovative solutions in industries such as business, healthcare, and technology.

Curriculum and Skills Gained in Masters in Data Analytics Online Programs

The curriculum in online Master’s in Data Analytics programs is designed to equip students with advanced analytical skills and strategic insights. It covers diverse aspects of data analytics, emphasizing real-world applications. The curriculum aims to prepare graduates for leadership roles in navigating the complexities of data-driven decision-making in various industries.  Here are some examples of courses commonly found in Master’s in Data Analytics Online programs:

• Data Analytics Fundamentals
  This course introduces students to foundational concepts, tools, and techniques for effective data analysis. Covering statistical methods, data manipulation, and visualization, the course establishes a solid understanding of the fundamental principles that underpin advanced analytics in various professional contexts.
• Statistics
  This course explores advanced statistical methods essential for practical data interpretation. Students delve into probability theory, hypothesis testing, regression analysis, and other statistical techniques, gaining crucial skills to extract meaningful insights and make informed decisions in data-driven environments.
• Big Data
  This course focuses on handling vast and complex datasets. Students learn scalable processing techniques, data storage solutions, and analytics tools. The course equips them to harness the potential of big data, addressing challenges and extracting valuable insights for informed decision-making in various industries.
• Introduction to Probability and Statistics
  This course provides a foundational understanding of statistical concepts and probability theory. Students explore vital principles, enhancing their analytical skills for data interpretation, hypothesis testing, and decision-making in the dynamic field of data analytics.
• Data Mining
  This course explores advanced techniques for discovering patterns and knowledge from large datasets. Students learn data preprocessing, modeling, and evaluation methods, honing their skills to extract valuable insights and make data-driven predictions crucial for informed decision-making in diverse professional domains.

 Upon graduation, students can expect to gain the following skills and learning outcomes:

• Data Analysis: Proficient in extracting insights from diverse datasets.
• Statistical Modeling: Application of statistical methods for predictive analysis.
• Data Visualization: Effectively communicate findings through visual representation.
• Machine Learning: Implementing algorithms for pattern recognition and prediction.
• Programming: Competent in languages like Python, R, or SQL for data manipulation.
• Database Management: Skillful handling and querying of databases.
• Big Data Technologies: Familiarity with tools for processing and analyzing large datasets.
• Critical Thinking: Strategic and analytical approach to data challenges.
• Communication Skills: Effectively convey complex findings to diverse audiences.
• Ethical Data Usage: Understanding and adhering to ethical considerations in data analytics.

Masters in Data Analytics Degree Types

There would typically be a few variants of a master’s in data analytics, with a few subjects changing concerning the specialization being pursued. Master’s in Data Analytics programs mainly come in three-degree formats – MS in Data Analytics, MPS in Analytics, and MBA in Data Analytics. Below, we will discuss the different types of master’s that can be pursued in data analytics.

Difference between Data Analytics, Data Science, and Business Analytics Programs

When some are trying to start a career in a data-related field, students are often confused about the difference between data analytics and data science. Despite being interconnected, they provide different results and pursue different approaches. Here, we will discuss their differences and look at what each delivers. Furthermore, we will also discuss the difference between data analytics and business analytics.

Data analysis involves answering questions generated for better business decision-making. It uses existing information to uncover actionable data. Data analytics focuses on specific areas with specific goals. On the other hand, data science focuses on discovering new questions one might not have realized answering to drive innovation. Unlike data analytics, which involves checking a hypothesis, data science tries to build connections, shaping the questions to answer them for the future. If we used the analogy of a house, it would be safe to say that If data science is a home for all the methods and tools, data analytics is a small room in that house. Data analytics is more specific and could be considered a special and concentrated field of data science.

Data analytics focuses more on viewing the historical data in context, while data science focuses more on machine learning and predictive modeling. Data science is a multi-disciplinary blend that involves algorithm development, data inference, and predictive modeling to solve analytically complex business problems. On the other hand, data analytics involves a few different branches of broader statistics and analysis.

Data Analytics vs. Business Analytics: Understanding the Difference

Data analytics involves analyzing datasets to uncover trends and insights to make informed organizational decisions. Business analytics focuses on analyzing various types of information to make practical, data-driven business decisions and implement changes based on those decisions. Business Analytics often uses insights drawn from data analysis to identify problems and find solutions.

While data analysts and business analysts work with data, the main difference lies in what they do with it. Business analysts use data to help organizations make more effective business decisions. In contrast, data analysts are more interested in gathering and analyzing data to evaluate and make decisions independently.

Specializations in Masters in Data Analytics Programs

Masters in Data Analytics students benefit from specialized coursework tailored to real-world applications. These focused studies enhance their analytical skills, making graduates adept at handling complex datasets. The practical knowledge gained prepares them for dynamic roles in industries where data-driven decision-making is essential. Specializations empower students to navigate the evolving data analytics landscape, cultivating adaptable and highly sought-after expertise. Below is a list of a few master’s in data analytics courses with specialization and career paths post-graduation:

Area of Focus	Description	Careers This Concentration prepares for
Machine Learning	This specialization explores advanced algorithms, statistical models, and computational methods. Students gain expertise in creating systems that learn from data, enabling them to develop predictive models, uncover patterns, and make informed decisions, fostering proficiency in the dynamic field of machine learning applications.	• Machine Learning Engineers • Data Scientists • Artificial Intelligence (AI) Research Scientists
Business Analytics	This specialization focuses on extracting actionable insights from business data. Students learn to apply statistical methods, data modeling, and predictive analytics to enhance finance, marketing, and operations decision-making. This specialization equips graduates to drive strategic initiatives and optimize business performance through data-driven approaches.	• Business Analysts • Operations Analysts • Marketing Analysts
Healthcare Analytics	This specialization explores the application of data analysis in the healthcare industry. Students learn to leverage data to improve patient outcomes, optimize healthcare processes, and make informed decisions. This specialization equips graduates with skills to address complex challenges in healthcare delivery and management through data-driven insights.	• Healthcare Data Analysts • Clinical Informatics Specialists • Healthcare Analytics Consultants
Financial Analytics	This specialization focuses on utilizing data analysis to make informed financial decisions. Students learn to apply statistical methods and predictive modeling to interpret financial data, manage risks, and optimize investment strategies. This specialization equips graduates to navigate the complexities of financial markets and enhance decision-making in the finance industry.	• Financial Analysts • Quantitative Analysts • Risk Analysts
Supply Chain Analytics	This specialization concentrates on optimizing and enhancing supply chain processes through data-driven insights. Students learn to analyze and interpret procurement, logistics, and inventory management data, enabling informed decision-making for efficient and resilient supply chain operations. This specialization equips graduates to address challenges and implement improvements in the dynamic field of supply chain management.	• Supply Chain Analyst • Logistics Analyst • Procurement Analyst • Operations Analyst • Demand Planner

Timeline for graduation from Masters in Data Analytics Online Programs

Most master’s in data analytics online typically takes anywhere between 16-24 months, while many accelerated master’s programs require just one year of study after students have completed their bachelor’s. In doing an accelerated program, students can save money on tuition. Typically, for a master’s in data analytics, students need to take 30 – 36 hours of credits.

1-Year Masters in Data Analytics Online Programs

Some experienced hands in the data analytics domain would benefit from a fast-track master’s in data analytics online program. But these programs are very rigorous and fast-paced and hence not for someone not versed in the discipline. These accelerated programs are similar to the 1-year MBA degrees. Here are a few universities that offer 1-year Master’s in Data Analytics Online programs:

• University of North Texas ¹
• Southern New Hampshire University ²
• Western Governor’s University³

Admission requirements vary from one university to another for a Master’s in Data Analytics Online. Most colleges generally require an undergraduate degree in data analytics or related fields. Since master’s programs require advanced coursework, institutions typically ensure students have a foundational understanding of data analytics. Furthermore, some programs may require the GRE test scores. Here are some of the standard admission requirements for the program:

• Bachelor’s Degree: Typically in data analytics or a related field.
• Minimum GPA: Requirements may vary.
• Letters of Recommendation: Usually 2-3.
• Statement of Purpose: Outlining career goals and reasons for pursuing the program.
• Resume: Highlighting relevant work experience.
• GRE/GMAT Scores: Some programs may require standardized test scores.
• Work Experience: Required by some programs but not all.

Accreditation means that an institution has been evaluated by an independent accrediting body and found to meet the high standards of a rigorous education. Thus, accreditation is the enforcement of quality. Unviservisites are often institutionally accredited by one of the federally recognized accreditors ⁴ for students to be eligible for U.S. federal student aid ⁵ . These accreditors are:

• New England Commission of Higher Education (NECHE)
• Middle States Commission on Higher Education (MSCHE)
• Higher Learning Commission (HLC)
• Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)
• Northwest Commission on Colleges and Universities (NWCCU)
• Western Association of Schools and Colleges (WASC) Senior College and University Commission (WSCUC)

AACSB Accredited International ⁶ is one organization that accredits data analytics master’s programs. It is a global non-profit association that connects educators, students, and businesses to achieve a common goal: creating the next generation of great leaders.
Find out more about accreditation in the Accreditation Guide.

Free Courses for Online Masters in Digital Strategy

 Free online courses do not result in a master’s degree; nonetheless, they can prove valuable for students in their day-to-day studies, assignments, exams, and capstone projects. Numerous free courses online, often created or offered by prestigious universities worldwide, offer information and insights that may not be readily available in traditional classrooms or textbooks. For students pursuing a master’s degree in digital analytics, here are some platforms providing free courses:

Course	Description	Provided by
Introduction to Data Analytics with Python 7	This course introduces the fundamentals of data analytics, encompassing key elements of Python programming. It explores various opportunities arising from the study of data analytics, such as assessing credit risks and advancing pharmaceutical research. Upon completion, one will comprehensively understand major data analytics types.	Alison
Introduction to Transforming with Data Analytics and the Digital Organization 8	This course provides a framework to navigate challenges posed by digital transformation successfully. Students learn how to use dynamic capabilities within the organization to initiate digital transformation. Second, utilize fitness landscapes to construct a competitive digital business model. Finally, implement a strategic foresight function to evolve the digital business model for continued organizational success.	edX
Descriptive Statistics with Excel for Data Analytics 9	This course is a practical guide for individuals passionate about pursuing a career as a data analyst. Learners will not only acquire quantitative statistical methods but also understand the underlying reasons and gain the ability to interpret data linguistically and in terms of statistical values and concepts.	Udemy

Post a master’s in data science online, one can delve into many roles in the data field. This could vary from a data analyst role at an entry level to a Chief Technology Officer (CTO) role at the top of the hierarchy. There would be other intermediatory roles in between. Below is a list of roles and salaries with their responsibilities outlines:

Occupation	Median Annual Salary	Job Growth (up to 2032)	Job Description
Information  Security Analyst 12	$112,000	32% (much faster than average)	The incumbent assists with setting up machine learning techniques for cybersecurity risk reporting and alerts and helps to alert the university of potential cyber threats.
Market Research/Research Data Analyst 13	$68,230	13% (much faster than average)	Research Data Analyst acquires skills and knowledge of professional concepts in research data analysis, focusing on machine and deep learning.
Computer and Information Research Scientists 14	$136,620	23% (much faster than average)	Computer and information research scientists devise creative applications for emerging and established technologies. They analyze and address intricate computing challenges across various sectors, including business, science, medicine, and beyond.
Equity Research Data Analyst 15	$111,875	No Data Available	Leads the planning and implementation of program evaluation and equity analysis projects, facilitating and identifying the scope, goals, and deliverables and providing analysis and reports. Establish data collecting and management procedures that allow for formative and summative assessment of the Division of Student Affairs and Success and HSI Initiatives.

Data analysts typically don’t need a certification or a mandatory license to practice their craft. However, organizations put a lot of value on professional certifications while hiring candidates. If one has completed a master’s in data analytics, pursuing one of the certifications relating to their field of work or a graduate certificate in data analytics would not be a bad idea. A few of them are listed below:

Certification	Description
Associate Certified Analytics Professional (ACAP) 16	The Associate Certified Analytics Professional (aCAP) credential is an entry-level analytics certification showing education in analytics. However, the individual may not have practical experience yet. The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management.
Certified Analytics Professional 17	The Certified Analytics Professional (CAP) credential is a general analytics certification that certifies end-to-end understanding of the analytics process, from framing business and analytic problems to acquiring data, methodology, model building, deployment, and model lifecycle management. It requires completing the CAP exam and adhering to the CAP Code of Ethics.
Cloudera Certified Associate (CCA) Data Analyst 18	A SQL developer who earns the CCA Data Analyst certification demonstrates core analyst skills to load, transform, and model Hadoop data to define relationships and extract meaningful results from the raw output. It requires passing the CCA Data Analyst Exam (CCA159), a remote-proctored set of eight to 12 performance-based, hands-on tasks on a CDH 5 cluster. Candidates have 120 minutes to implement a technical solution for each task.
Data Analyst Associate19	The Data Analyst Associate certification is one of several role-based certifications that replace the Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics certification that Microsoft retired in January 2023. This certificate demonstrates subject matter expertise in enabling businesses to leverage their data assets using Microsoft Power BI.
Open Certified Data Scientist 20	The Open CDS is an independent global certification that qualifies data scientists’ skills, knowledge, and experience. Open CDS requires candidates to demonstrate their skills and expertise against conformance requirements through written applications and peer interviews. It does not include training courses, and there are no written exams.

Post a master’s in data analytics online, data analytics professionals can further their careers and remain relevant in this fast-paced industry by becoming members and hence accrediting themselves with a professional organization in the field of data analytics.  Apart from being a body that assists in developing and distributing knowledge, professional data science associations keep their members informed about the newest developments and innovations. Here are a few of such organizations:

Professional Organization	Description
Association of Data Scientists (ADaSci)	The Association of Data Scientists (ADaSci) is the leading global body of data science and machine learning professionals. Association of Data Scientists (ADaSci) serves the scientific and professional demands of data science among professionals, including scientists, students, educators, analysts, managers, and consultants.
The American Statistical Association	The American Statistical Association is the world’s biggest community of statisticians. It is the second oldest continuously running professional association in the US and was created in Boston in 1839. Its members work in corporate, government, and academia in more than 90 countries, advancing research and developing quality data and statistical work to inform public policy.
The Data Science Council of America (DASCA)	The Data Science Council of America (DASCA) is a global independent, third-party association for credentialing Big Data professionals. The Data Science Council of America (DASCA) has developed platform-independent Data Science knowledge frameworks, standards, and credentials. It certifies people starting or working across a range of emerging Data Science professions.
The Institute for Operations Research and the Management Sciences	The Institute for Operations Research and the Management Sciences (INFORMS) is a worldwide society for practitioners in operations research (OR), management science, and analytics and was established in 1995.