M.S. in Data Analytics
32
Credit Hours
19
Months (Avg.)
Class Type
Next Start Date
Aug 15, 2022
Placement Tests
GMAT/GRE not required for admission
Embedded Credentials
Graduate Certificate

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

On Site

Finish in 19 Months

Earn your degree and prepare for advancement faster.

100% Online Coursework Available

Balance earning your degree with other work-life commitments.

Hands-On Learning

Build your skills using industry-leading tools and programming and modeling techniques.

No GMAT or GRE

Bypass expensive, time-consuming tests and get started sooner.

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)

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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!"

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 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.

COMP 630 - Issues in Database Management (4)

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.

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 linear and logistic regression, probabilistic inference, Support Vector Machines, Artificial Neural Networks, clustering, and dimensionality reduction, and programming.

DATA 612 - Computing for Data Analytics (4)

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.

DATA 621 - Advanced Analytics (4)

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.

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.

Corequisites
MATH 215 - Statistical Concepts (4)

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.

Complete the above course or the equivalent from an accredited school. Prerequisite must be completed with a grade of C or better.

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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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.

Master's in Data Analytics Program Details

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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 specialists analyze data and advise organizations on how to best manage resources without sacrificing quality. 
 

Employment Outlook

9%

From 2021-2031 jobs in Data Analytics are expected to increase by 9%

All Occupations

2021
487,405 jobs
2031
533,406 jobs
Show Details >

Statisticians

2021
43,954 jobs
2031
57,274 jobs

Statistical Assistants

2021
10,685 jobs
2031
11,299 jobs


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

Data Analytics Knowledge & Skillsets

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

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