M.S. in Data Analytics

Credit Hours

Month Completion

Class Type

100% onlineSee state availability

Next Start Date

Jan 6, 2025

Placement Tests

GMAT/GRE not required for admission

Embedded Credentials

Graduate Certificate

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Home / Degrees / Master's Degrees / Data Analytics

Translate chaotic data sets into competitive advantage with a master’s in data analytics

With on-going expansion of modern technology including smart devices, social networking, online shopping and more, the amount of data captured is growing exponentially. While the collection and storage of these large amounts of data has become easier and inexpensive, the demand for individuals with the skills capable of managing, analyzing and mining this information is surging. The M.S. in Data Analytics equips you with the statistical skills necessary to conduct descriptive and predictive analytics; the programming skills to create and apply computer algorithms; the tools and platforms to visualize and mine big data, and the communication skills necessary to effectively convey findings and provide strategies and best practices within your organization.

Program Availability

Online

On Site

M.S. in Data Analytics Degree Overview

Earn a degree aligned with industry demand

Organizations from all sectors of the economy are seeking individuals with programming, analytics and communication skills for the purpose of sorting immense data sets to provide a competitive edge or a predictive tool that will help differentiate themselves in crowded markets. Demand for data analytics professionals is also expected to continue to grow by 9%.* In addition, a survey of job postings nationwide shows that data analytics jobs take longer to fill compared to other positions, indicating that demand is high and supply is low for qualified individuals to fill these positions.

Franklin’s transfer-friendly M.S. in Data Analytics enables you to take advantage of the rising demand for analytics skills and effectively prepares you for the analytics-related jobs of today and tomorrow. The robust curriculum includes coursework in statistics, programming, data management, data visualization, data mining, machine learning and advanced analytics.

Build technical skills with hands-on exposure to industry-standard tools

As a student in the M.S. in Data Analytics, you will be exposed to cutting-edge technology and techniques to address the most common challenges within the discipline. You’ll explore big data technologies including Hadoop, MapReduce, Data Warehouse, SQL, No SQL and In-memory Databases.

You’ll build proficiency that translates into a competitive advantage in the job market thanks to the heavy integration of industry-standard tools and techniques like Python and R to learn data processing algorithms and Tableau to complete hands-on projects and assignments.

Earn a high-quality, comprehensive master’s in data analytics 100% online

At Franklin, you’ll get the convenience and flexibility of a quality online education, expert instructors who have relevant and real-world experience, and strong student support from dedicated faculty, tutors and advisors.

As you progress through the program, you’ll learn to manage, visualize and analyze complex data sets; apply a number of analytics methods to solve business problems and effectively communicate your results through a combination of interactive and relevant coursework. The capstone project gives you an opportunity to integrate and synthesize the skills and knowledge you gained throughout the program.

Transfer up to 12 credits and finish your master’s faster

If you have already taken graduate-level courses, you may be able to transfer credit and save time and money toward your master’s degree. Franklin offers course-for-course credit for every class within the M.S. Data Analytics – except the capstone (BUSA 695). To see if your previous coursework can be used to satisfy degree requirements, you’ll need to submit a syllabus for the course(s) you’d like to have evaluated for transfer credit. Your admissions advisor will be happy to assist you in any way.

*Source information provided by Economic Modeling Specialists International (EMSI)

Future Start Dates

Spring 2025

January

Recommended Register By:

Dec 27

Spring 2025

January

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Jan 17

Spring 2025

February

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Feb 7

Summer 2025

May

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May 9

Fall 2025

August

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Aug 8

Fall 2025

September

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Aug 29

Fall 2025

September

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Sep 19

Spring 2026

January

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Dec 26

Summer 2026

May

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May 8

Fall 2026

August

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Aug 7

Fall 2026

September

Recommended Register By:

Aug 28

Your Best Value M.S. in Data Analytics

Affordable Tuition

$670

PER CREDIT HOUR

Get ahead without going broke.

Finish Fast

MONTHS TO COMPLETE

Realize your career goals sooner and reap the benefits.

Non-Profit = Student Focused

Unlike for-profit universities, Franklin invests in student success, not shareholder gain.

Tuition Guarantee

Inflation-proof your degree cost by locking-in your tuition rate from day one through graduation.

Highly Recommended

98%

STUDENT SATISFACTION

98% of graduating students would recommend Franklin to their family, friends and/or colleagues.

Source: Franklin University, Office of Career Development Student Satisfaction Survey (Summer 2023)

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Search below to see if you could save tuition through an employer or professional organization partnership.

$21,440

Total Tuition
(After Partner Discount)

Data Analytics Courses & Curriculum

32 Semester Hours

Major Area Required

MATH 601 - Introduction to Analytics (4)

This course provides an introductory overview of methods, concepts, and current practices in the growing field of statistics and data analytics. Topics to be covered include data collection, data analysis and visualization as well as probability, statistical inference and regression methods for informed decision-making. Students will explore these topics with current statistical software. Some emphasis will also be given to ethical principles of data analytics.

DATA 605 - Data Visualization & Reporting (4)

This course focuses on collecting, preparing, and analyzing data to create visualizations, dashboards, and stories that can be used to communicate critical business insights. Students will learn how to structure and streamline data analysis projects and highlight their implications efficiently using the most popular visualization tools used by businesses today.

DATA 610 - Big Data Analytics and Data Mining (4)

This course explores data mining methods and tools, examines the issues in the analytical analysis of massive datasets, and unstructured data. Students will learn the concepts and techniques to discover the patterns in large datasets, which support organizational decision making.

DATA 611 - Applied Machine Learning (4)

This course explores two main areas of machine learning: supervised and unsupervised. Topics include the fundamental concepts, roadmap of a machine learning project, classification algorithms, regression algorithms, dimensionality reduction, model evaluation, natural language processing, neural networks and deep learning, typical issues in real-world machine learning problems, and Python programming in data science.

DATA 612 - Computing for Data Analytics (4)

This course explores data mining methods and procedures for diagnostic and predictive analytics. Topics include association rules, clustering algorithms, tools for classification, and ensemble methods.

DATA 621 - Advanced Analytics (4)

This course examines the data analysis process using some advanced statistical methods. Students will improve their skills in data analytics and predictive analytics which will allow them to develop algorithmic methods for decision-making using popular industry software for data-driven solutions.

DATA 695 - Capstone (4)

The purpose of this capstone course in Data Analytics is to assess students' ability to synthesize and integrate the knowledge and skills they have developed throughout their coursework. The course provides students with the opportunity to demonstrate competency on the key domains of data analytics through a comprehensive project including problem scoping, data preparation and analysis, and a model development.

DATA 630 - Applied Database Management (4)

This course teaches data management from an applied perspective. The topics include fundamentals of database management systems, structured query language (SQL) for data analytics, relational database design, and data warehousing.

Embedded Credentials Recognize Achievement in Real-Time

Embedded certificate marks midpoint to degree completion

Your time and tuition dollars pay off fast with a Graduate Certificate in Data Analytics awarded after the completion of your first four master’s courses.

Courses

Complete the courses below and receive a certificate that formally documents your ability to identify and communicate insights gained through data analysis.

MATH 601 - Introduction to Analytics
DATA 605 - Data Visualization and Reporting
DATA 610 - Big Data Analytics and Data Mining
DATA 630 - Applied Database Management

Microcredentials Align with Job Essentials

In today's dynamic work environments, adaptive professionals thrive. A microcredential - either as a stand-alone course or integrated into your degree program - is a short, skill-specific recognition that enables you to demonstrate your competency in a distinct area. Like Franklin's degree programs, microcredentials are aligned with market and industry demand to ensure what you learn can be put to use right away. Microcredentials are easily shared via digital badges and can be stacked to create a unique portfolio of in-demand skills.

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M.S. in Data Analytics Program Details

Tuition Costs

2024 - 2025 Tuition	Cost Per Credit
Standard tuition per credit hour	$670
Nursing programs MSN-FNP, MSN-PMHNP, MSN-AGPCNP, Post-Graduate FNP Certificate, Post-Graduate AGPCNP Certificate and Post-Graduate PMHNP Certificate	$670
MSN-Generalist, MSN-Nurse Administrator and MSN-Nurse Educator	$598
RN-MSN Pathway (NURS 500)	$298
Current service members	$536
Graduate Prerequisite Courses (500 level)	$398
Graduate Prerequisite Courses (500 level) - International Students	$526

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Program Learning Outcomes

A learning outcome map functions as a roadmap to help guide students' progress through their program of study. Click HERE to view the M.S. Data Analytics matrix.

Degree Requirements

To be awarded a graduate degree, students must:

Successfully complete all required curriculum courses.
Maintain a minimum cumulative grade point average (GPA) of 3.00.
Complete the residency requirement:
- Master of Science – Data Analytics students must earn at least 20 of the 32 required credits at Franklin University.
Complete the payment of all requisite tuition and fees;
Not to be under disciplinary dismissal due to academic dishonesty or violation of Student Code of Conduct.

Transfer credit awarded based on experiential learning shall not count toward the residence requirement at Franklin University.

Admission Requirements

The admission process reflects Franklin University’s efforts to clearly identify the performance standards that can help predict student success in graduate level study. The selection criterion for Franklin’s graduate programs, as determined by faculty, emphasizes academic ability, contributory work experience, and personal qualities and characteristics.

Requirements for admission include having earned a bachelor's degree from an institution accredited by the Accrediting Commission for Community and Junior Colleges, Western Association of Schools and Colleges (ACCJC), Higher Learning Commission (HLC), Middle States Commission on Higher Education (MSCHE), New England Commission on Higher Education (NECHE), Northwest Commission on Colleges and Universities (NWCCU), Southern Association of Colleges and School Commission on Colleges (SACSCOC), WASC Senior College and University Commission (WSCUC), or a Council for Higher Education Accreditation (CHEA)-recognized accrediting organization with a GPA of at least a 2.75 on a 4.0 scale.

Applicants who earned at least a 2.5 GPA on a 4.0 scale in their earned bachelor’s degree will automatically be granted conditional enrollment status. Applicants who earned lower than a 2.5 GPA on a 4.0 scale in their earned bachelor’s degree can petition for conditional enrollment status to the program chair by submitting an essay detailing other criteria that the applicant believes should be considered to demonstrate their ability to be successful in a graduate program. This petition could include details on the applicant’s work experience, work ethic, level of professionalism, personality characteristics, level of difficulty of program of study previously completed, etc.

Conditional enrollment requires students to achieve a final grade of “B” (3.0 GPA) or better in the first graduate-level course of their program. If the terms of the conditional enrollment are not met, the student will not be allowed to advance in their program and will be unable to earn this graduate degree from Franklin University.

English Language Testing & TOEFL IELTS

Prospective students must demonstrate English Language Proficiency. The requirement is met through any of the following:

The applicant is a citizen of a country where English is the official language.*
The applicant has received a bachelor’s degree (or higher) from an institution located in an English-speaking country in which the courses were taught in English.*
The applicant has earned appropriate scores on language proficiency exams taken within the last two years, as listed in the Academic Catalog.

*For more information about English proficiency, including a list of English-speaking nations, please visit our International Students section.

Program Advisory Board

The University employs a team approach to planning, developing and maintaining its academic curriculum. An essential element of this process – and a key to the institution’s quality assurance practices – is the Program Advisory Board (and the associated Alumni Advisory Board). A diverse array of business and industry leaders make up these discipline-specific boards that provide guidance on theory-to-practice ideas, global business perspectives, and emerging topics in the field. Each academic year, Program Advisory Boards meet with Division Chairs and faculty for lively and engaged conversations, thus bringing members’ substantial professional experience and expertise into the classroom. In addition, some Division Chairs elect to engage Program Advisory Board members in the assessment of academic program outcomes.

Name	Organization	Title
Erin Hamm	Comcast	Field Chief Data Officer
Paul Hendricks	NVIDIA	Senior Data Scientist
Micaela Parker	Academic Data Science Alliance	Founder and Executive Director
Rebecca Sela	J.P. Morgan Chase & Co.	Data Science Director
Loren Stone	Autonomy Hub	CEO+President
Christopher Wetherill	Equity Trust Company	Director of Data Engineering

Employment Outlook

30%

From 2023-2033, jobs in Data & Analytics are expected to increase by 30%

Occupation

Median Salary (2023)

Job Postings (2023)

Projected Growth (2023-2033)

Occupation

Data Scientists

$108,014

179,836

36%

Data Scientists

Median Salary: $108,014
Job Postings: 179,836
Projected Growth: 36%

Occupation

Job Titles

Skills

Industry

Description

Data Scientists develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

Projected Growth

Job Title	Job Postings	% of Job Postings
Data Analysts	49,486	28%
Data Scientists	46,356	26%
Business Intelligence Analysts	15,654	9%
Enterprise Architects	10,517	6%
Machine Learning Engineers	10,092	6%
Data Science Managers	4,821	3%
Data Analytics Managers	4,395	2%
Lead Data Scientists	3,763	2%
Data Modelers	2,769	2%
Principal Data Scientists	4,621	3%
Directors of Data Science	2,953	2%
Principal Architects	3,224	2%
Data Governance Analysts	2,765	2%
SAP Functional Analysts	2,395	1%
SAP Consultants	1,939	1%
Machine Learning Software Engineers	3,031	2%
Solutions Architects	2,492	1%
Data Quality Analysts	2,256	1%
Enterprise Solutions Architects	2,966	2%
Modeling and Simulation Engineers	3,341	2%

Skill	Job Postings	% of Total Postings
Data Analysis	107,273	38%
SQL (Programming Language)	89,800	32%
Computer Science	85,532	30%
Python (Programming Language)	78,866	28%
Data Science	67,413	24%
Machine Learning	54,259	19%
Statistics	54,094	19%
Project Management	48,489	17%
R (Programming Language)	45,347	16%
Tableau (Business Intelligence Software)	44,041	16%
Business Process	43,004	15%
Business Requirements	38,709	14%
Dashboard	37,695	13%
Power BI	37,248	13%
Finance	36,498	13%
Data Visualization	35,738	13%
Business Intelligence	35,546	13%
SAP Applications	33,801	12%
Data Modeling	33,222	12%
Agile Methodology	33,103	12%

	Industry	% of Occupation in Industry
	Computer Systems Design and Related Services		12%
	Management of Companies and Enterprises		9%
	Management, Scientific, and Technical Consulting Services		7%
	Insurance Carriers		6%
	Scientific Research and Development Services		5%
	Depository Credit Intermediation		4%
	Other		57%

Statisticians

$104,104

18,840

30%

Statisticians

Median Salary: $104,104
Job Postings: 18,840
Projected Growth: 30%

Occupation

Job Titles

Skills

Industry

Description

Statisticians develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide usable information. May specialize in fields such as biostatistics, agricultural statistics, business statistics, or economic statistics. Includes mathematical and survey statisticians.

Projected Growth

Job Title	Job Postings	% of Job Postings
Biostatisticians	5,456	29%
Directors of Biostatistics	2,290	12%
Statisticians	1,935	10%
Biostatistics Managers	2,344	12%
Principal Biostatisticians	1,063	6%
Statistical Analysts	852	5%
Statisticians/Data Scientists	610	3%
Statistical Programming Managers	718	4%
Research Statisticians	475	3%
Mathematical Statisticians	427	2%
Statistical Data Analysts	370	2%
Biometricians	311	2%
Principals	264	1%
Survey Statisticians	272	1%
Statistical Research Analysts	263	1%
Statistical Scientists	221	1%
Research Biostatisticians	259	1%
Statistical Programmers	235	1%
Statistical Programming Analysts	304	2%
Directors of Statistics	171	1%

Skill	Job Postings	% of Total Postings
Statistics	10,070	80%
SAS (Software)	6,679	53%
Biostatistics	6,621	52%
Statistical Analysis	6,172	49%
R (Programming Language)	5,312	42%
Clinical Trials	5,116	41%
Data Analysis	4,669	37%
Statistical Methods	3,756	30%
Statistical Programming	2,976	24%
Pharmaceuticals	2,919	23%
Data Management	2,671	21%
Clinical Study Design	2,474	20%
Python (Programming Language)	2,401	19%
Data Science	2,388	19%
Statistical Software	2,280	18%
Project Management	2,202	17%
Pre-Clinical Development	2,102	17%
Data Collection	1,891	15%
Computer Science	1,794	14%
Drug Development	1,739	14%

	Industry	% of Occupation in Industry
	Federal Government, Civilian		19%
	Scientific Research and Development Services		17%
	Education and Hospitals (State Government)		7%
	State Government, Excluding Education and Hospitals		7%
	Colleges, Universities, and Professional Schools		6%
	Computer Systems Design and Related Services		6%
	Other		38%

Operations Research Analysts

$83,637

36,955

23%

Operations Research Analysts

Median Salary: $83,637
Job Postings: 36,955
Projected Growth: 23%

Occupation

Job Titles

Skills

Industry

Description

Operations Research Analysts formulate and apply mathematical modeling and other optimizing methods to develop and interpret information that assists management with decisionmaking, policy formulation, or other managerial functions. May collect and analyze data and develop decision support software, services, or products. May develop and supply optimal time, cost, or logistics networks for program evaluation, review, or implementation.

Projected Growth

Job Title	Job Postings	% of Job Postings
Operations Analysts	8,552	23%
Sales Operations Analysts	4,432	12%
Operations Research Analysts	2,924	8%
Continuous Improvement Managers	2,395	7%
Process Improvement Managers	1,341	4%
Process Improvement Analysts	1,530	4%
Surgeons	6,015	16%
Business Process Managers	1,506	4%
Methodologists	917	3%
Decision Support Analysts	965	3%
IT Operations Analysts	886	2%
Revenue Operations Analysts	730	2%
Operations Support Analysts	724	2%
Process Excellence Managers	524	1%
Investment Operations Analysts	618	2%
Cybersecurity Operations Analysts	605	2%
Decision Science Analysts	670	2%
Process Analysts	533	1%
Process Managers	674	2%
Business Process Improvement Managers	414	1%

Skill	Job Postings	% of Total Postings
Project Management	12,028	21%
Process Improvement	11,855	21%
Data Analysis	9,827	17%
Finance	8,838	15%
Continuous Improvement Process	7,339	13%
Auditing	6,075	11%
Business Process	6,061	11%
Workflow Management	5,249	9%
SQL (Programming Language)	5,225	9%
Accounting	5,047	9%
Key Performance Indicators (KPIs)	4,955	9%
Marketing	4,262	7%
Computer Science	3,982	7%
Dashboard	3,892	7%
Supply Chain	3,822	7%
Automation	3,800	7%
Operations Research	3,752	7%
Statistics	3,628	6%
Salesforce	3,461	6%
Tableau (Business Intelligence Software)	3,436	6%

	Industry	% of Occupation in Industry
	State Government, Excluding Education and Hospitals		13%
	Management of Companies and Enterprises		10%
	Depository Credit Intermediation		8%
	Federal Government, Civilian		6%
	Management, Scientific, and Technical Consulting Services		6%
	Computer Systems Design and Related Services		6%
	Other		51%

Statistical Assistants

$50,523

250

Statistical Assistants

Median Salary: $50,523
Job Postings: 250
Projected Growth: 2%

Occupation

Job Titles

Skills

Industry

Description

Statistical Assistants compile and compute data according to statistical formulas for use in statistical studies. May perform actuarial computations and compile charts and graphs for use by actuaries. Includes actuarial clerks.

Projected Growth

Job Title	Job Postings	% of Job Postings
Statistical Analysts	149	60%
Assistant Professors of Mathematics	16	6%
Assistant Professors of Political Science	12	5%
Mathematics Assistant Professors	5	2%
Tenure-Track Professors	9	4%
Assistant Professors of Statistics	4	2%
IT Student Assistants	7	3%
Statistical Scientists	4	2%
Assistant/Associate/Full Professors	4	2%
Clinical Assistant Professors	5	2%
Mathematical Statisticians	4	2%
Directors of Data Science	10	4%
Environmental Scientists	2	1%
Financial Reporting and Analysis Managers	7	3%
Mathematics Teaching Assistants	1	0%
Occupational Therapy Assistants	2	1%
Quantitative Analytics Managers	2	1%
Statistical Research Analysts	2	1%
Statistical Research Assistants	3	1%
Technical Resource Specialists	2	1%

Skill	Job Postings	% of Total Postings
Statistics	141	94%
Data Analysis	114	76%
Statistical Analysis	104	69%
Data Mining	103	69%
Data Structures	103	69%
Software Development	103	69%
Usability	103	69%
SAS (Software)	101	67%
Computer Programming	100	67%
Python (Programming Language)	100	67%
R (Programming Language)	100	67%
C# (Programming Language)	99	66%
Java (Programming Language)	99	66%
Structured Programming	99	66%
Version Control	99	66%
Task Management	97	65%
Data Science	22	15%
Mathematical Statistics	15	10%
Algebra	12	8%
Biostatistics	12	8%

	Industry	% of Occupation in Industry
	Scientific Research and Development Services		12%
	Computer Systems Design and Related Services		10%
	Colleges, Universities, and Professional Schools		10%
	Federal Government, Civilian		10%
	Insurance Carriers		9%
	State Government, Excluding Education and Hospitals		8%
	Other		41%

Source: Employment Outlook data is provided by Lightcast. Franklin University cannot guarantee employment placement, salary level, or career advancement.

Data Analytics Knowledge & Skillsets

Gain in-demand skills sought by employers with curriculum that teaches you:

Data Analysis

Interpret data and recommend appropriate course of action to improve effectiveness
Analyze information to produce analytically driven inferences and insights to generate actionable recommendations
Interpret results of analysis; present recommendations, including alternatives and implications
Conduct benchmarking, trend analysis and other input to drive continuous improvement and elevate performance
Analyze requirements, procedures and problems to automate processing or to improve existing business systems

Database Design & Development

Design, model, and build data structures and data mapping routines to support data and reporting requirements
Administer and monitor systems in the purview of information security
Update, review and maintain operational database systems
Examine the techniques and issues involved in securing databases
Predict new trends in database management
Investigate techniques for measuring the effectiveness of database design
Experiment with techniques for the optimization of database queries

Business & Management

Develop technical solutions to business problems and measure outcomes
Analyze and evaluate management systems for improvement
Analyze financial statements for trends and performance against expectations
Analyze business conditions, including pricing, cost and budget consequent to engage in strategic planning and decision
Analyze the external business environment to determine strengths, weaknesses, opportunities and threats
Write technically proficient quantitative surveys, across a wide array of topic areas and with varying degrees of complexity

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Data Analytics Options

M.S. in Data Analytics

M.S. in Computer Science Data Analytics Focus

M.S. in Information Technology - Data Analytics Focus

Focus:
Develop proficiency in using data as a predictive tool for solving business challenges and creating a competitive advantage.

Skills:
Learn to use and apply descriptive and predictive analytics, data visualization and computer algorithms.

Careers:
Apply your M.S. in Data Analytics to help organizations use data to maximize operations, inform decision making and optimize financial performance.

How many courses are in the program?
Eight 12-week courses

How quickly can I complete the program?
19 months

Learn More

Focus:
Enhance your expertise as you combine the principles of computer science with the elements of data modeling to facilitate knowledge discovery and application.

Skills:
Develop in-demand skills in the areas of database design, data mining, statistical analysis and visual storytelling.

Careers:
Put your M.S. in Computer Science-Data Analytics to work helping organizations leverage data-informed insights for business growth and success.

How many courses are in the program?
Nine 12-week courses

How quickly can I complete the program?
20 months

Learn More

Focus:
Grow your skills as a technologist that uses data and statistical reasoning to identify trends, make predictions and inform decision making.

Skills:
Strengthen your understanding and application of statistical inference methodologies, data mining tools and techniques, and visual-based reporting.

Careers:
Use your M.S. in IT-Data Analytics to help organizations understand and apply data to enhance position, demonstrate value, and improve profitability.

How many courses are in the program?
Nine 12-week courses

How quickly can I complete the program?
16 months

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Data Analytics Frequently Asked Questions

What is an M.S. in Data Analytics degree?

The M.S. in Data Analytics is focused on the science of data – coding, modeling and analytic tools – and data operations including advanced analysis. Data analytics professionals use mathematical and statistical methods and techniques along with programming to design and build data models.

What can you do with M.S. in Data Analytics degree?

The M.S. Data Analytics equips you with the statistical skills necessary to conduct descriptive and predictive analytics; the programming skills to create and apply computer algorithms; the tools and platforms to visualize and mine big data, and the communication skills necessary to effectively convey findings and provide strategies and best practices within your organization.

Why get an M.S. in Data Analytics degree?

What makes Franklin’s M.S. in Data Analytics degree unique?

Coursework for Franklin’s 19-month accelerated M.S. in Data Analytics program can be completed 100% online. Through our partnership with SAS, a global leader in analytics, you’ll also earn a SAS Tier 2 Academic Specialization in Data Analytics, which will complement your master’s degree and underscore your analytic knowledge and abilities.

How long does it take to get M.S. in Data Analytics degree?

Franklin's M.S. in Data Analytics can be completed in 19 months, 100% online.

When can I start an M.S. in Data Analytics degree?

The M.S. in Data Analytics has multiple start dates per year.

How much will my M.S. in Data Analytics degree cost?

Franklin University offers a quality education at a competitive cost so you can afford to invest in your future. Our per credit hour tuition rates (vs. per year or per term rates) enable you to better anticipate your tuition costs. Our 2024-2025 tuition rate is $670 per credit hour and you can use Franklin’s free online MyCost Estimator tool to get a personalized estimate of your total degree cost. Ask our helpful staff about available financing options and financial aid programs.

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Columbus, OH 43215

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Embedded Credentials

Translate chaotic data sets into competitive advantage with a master’s in data analytics

Finish in 19 Months

100% Online Coursework

Hands-On Learning

Learn from the Best

Earn a degree aligned with industry demand

Build technical skills with hands-on exposure to industry-standard tools

Earn a high-quality, comprehensive master’s in data analytics 100% online

Transfer up to 12 credits and finish your master’s faster

Melanie M.

M.S. Data Analytics '21

Affordable Tuition

Finish Fast

Non-Profit = Student Focused

Tuition Guarantee

Highly Recommended

Partner? Pay Less.

Embedded certificate marks midpoint to degree completion

Know the Total Cost of Your Master’s from Day One

English Language Testing & TOEFL IELTS

Free Big Data Career Guide

From 2023-2033, jobs in Data & Analytics are expected to increase by 30%

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