Class Type100% onlineSee state availability
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About Start Dates
Additional future start dates include:
Fall 2023
Sep 25, 2023Start dates for individual programs may vary and are subject to change. Please request free information & speak with an admission advisor for the latest program start dates.
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Embedded Credentials
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
Finish in 19 Months
Earn your degree and prepare for advancement faster.
100% Online Coursework
Balance earning your degree with other work-life commitments.
Hands-On Learning
Build your skills using industry-leading tools and programming and modeling techniques.
Learn from the Best
Benefit from the experience of your instructors – seasoned, in-field practitioners.
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)
Melanie M.
M.S. Data Analytics '21
"I was able to advance in my career while working full time and watching my newborn at home full time. This has been the greatest accomplishment for me!"
Future Start Dates
Start dates for individual programs may vary and are subject to change. Please request free information & speak with an admission advisor for the latest program start dates.
Your Best Value M.S. in Data Analytics
Choose Franklin's M.S. in Data Analytics and get a high-quality degree that fits your life and your budget.
Affordable Tuition
Get ahead without going broke.
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
97% of graduating students would recommend Franklin to their family, friends and/or colleagues.
Source: Franklin University, Office of Career Development Student Satisfaction Survey (Fall 2021)
Data Analytics Courses & Curriculum
This course provides an introductory overview of methods, concepts and current practices in the growing field of Data Analytics. Topics to be covered include data collection, analysis and visualization as well as statistical inference 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.
This course focuses on the fundamental design considerations in designing a database. Specific topics include performance analysis of design alternatives, system configuration and the administration of a popular database system. The course also offers an in-depth analysis of the algorithms and machine organizations of database systems. Note, this course has proctored exam(s). This exams requires additional technology, if student uses online proctoring.
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.
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.
This course explores two main areas of machine learning: supervised and unsupervised. Topics include linear and logistic regression, probabilistic inference, Support Vector Machines, Artificial Neural Networks, clustering, and dimensionality reduction, and programming.
This course explores the methods of analytics computing and the procedures for diagnostic and predictive analytics. Topics include data manipulation, clustering algorithms, and regression methods using basic programming techniques.
This course examines the data analysis process with the emphasis of quantitative and qualitative findings from data. Students will develop skills in data analytics methods and predictive analytics that will allow them to develop algorithmic methods and use them along with popular industry software for data-driven solutions.
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.
This course introduces the student to statistics with business applications. The course covers both descriptive and inferential statistics. Topics included are: measures of central tendency; measures of dispersion; graphical displays of data; linear regression; basic probability concepts; binomial and normal probability distributions; confidence intervals; and hypothesis testing. These topics will be covered using a basic knowledge of algebra and Microsoft Excel. Note, this course has proctored exam(s).
Complete the above course or the equivalent from an accredited school. Prerequisite must be completed with a grade of C or better.
Embedded Credentials Recognize Achievement in Real-Time
Embedded credentials provide a quick ROI on the time and tuition you’re investing in your master’s degree.
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.
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
- COMP 630 - Issues in Database Management
- DATA 605 - Data Visualization and Reporting
- DATA 610 - Big Data Analytics and Data Mining
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.
Master's in Data Analytics Program Details
| 2021 - 2022 Tuition | Cost Per Credit |
|---|---|
| Standard tuition per credit hour | $670 |
| Current service members | $536 |
| Graduate Prerequisite Courses (500 level) | $398 |
| Graduate Prerequisite Courses (500 level) - International Students | $526 |
| 2022 - 2023 Tuition | Cost Per Credit |
|---|---|
| Standard tuition per credit hour | $670 |
|
Nursing programs |
$670 |
| MSN-Generalist and MSN-Nurse Administrator | $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 |
Know the Total Cost of Your Master’s from Day One
Save yourself the anxiety of annual tuition increases with Franklin’s Tuition Guarantee. The guarantee lets you lock-in what you’ll pay from first-term through graduation, as long as you remain actively enrolled. Not only will this help you maximize funding sources - like employer reimbursement or financial aid, it will keep you focused on earning your degree.
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.
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.
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 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.
Program Corequisites
Successful completion (C or better) of a college level Introductory Statistics course is required. Completion of a college level programming course is strongly recommended.
Please note: A program requirement, MATH 601, has a prerequisite of MATH 215 Statistical Concepts, or equivalent.
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.
| Name | Organization | Title |
| Angela Stabler | SAS Institute | Analytical Training Consultant |
| Erin J. Hamm | Nationwide Insurance | Specialist, Data and Analytics |
| Gregor MacDonald | Nationwide Insurance | Executive Director, Mortgage CCAR and Retail Capital Modeling |
| Karl T. Leckrone | Scotts MiraceGro | Data Scientist |
| Rehgan Avon | Open Data Group | Solutions Architect |
| Paul Hendricks | NVIDIA | Senior Solutions Architect, Machine Learning and Deep Learning |
| David M. Sebert | Nationwide Insurance | Director, Business Process Optimization |
| Christopher Wetherill | State Auto Insurance | Lead Data Scientist |
Free Big Data Career Guide
Start or level-up your big data career with first-hand tips and expert advice from real-world pros.
Career Opportunities
Data Scientist
Data scientists collect data and prepare it for analysis by building statistical and predictive models.
Information Security Analyst
Information security analysts plan and implement security features to protect an organization’s computer networks and systems.
Business Intelligence Analyst
Business intelligence analysts use big and small data to predict trends that enable companies to increase profits and efficiency.
Data Warehousing Administrator
Data warehouse administrators manage the daily activities of a data warehouse including archiving, tracking data changes, migration and monitoring data systems.
Operations Research Analyst
Operations research analysts examine organizational operations to inform management decisions, policy changes and other adjustments to improve logistics and operational efficiency.
Employment Outlook
From 2021-2031 jobs in Data Analytics are expected to increase by 9%
All Occupations
| 2021 |
487,405 jobs
|
| 2031 |
533,406 jobs
|
Statisticians
| 2021 |
38,109 jobs
|
| 2031 |
49,246 jobs
|
Statistical Assistants
| 2021 |
10,685 jobs
|
| 2031 |
11,299 jobs
|
Source information provided by Lightcast.
Data Analytics Knowledge & Skillsets
Gain in-demand skills sought by employers with curriculum that teaches you:
- 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
- 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
- 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
Find the Data Analytics Program That Fits Your Goals
If you’re interested in advancing your technology career, Franklin has several great options. Compare programs and identify your perfect match.
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
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
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
Data Analytics Frequently Asked Questions
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.
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.
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 are also expected to continue to grow by 30%, a rate that’s faster than average.
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.
Franklin's M.S. in Data Analytics can be completed in 19 months, 100% online.
The M.S. in Data Analytics has multiple start dates per year.
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 2022-2023 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.
Investigate Your Options
Interested in a career that focuses on data and information, but not quite sure where you fit?
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