M.S. in 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.

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Distinguish yourself as a top-notch talent with a SAS Tier 2 Academic Specialization in Data Analytics. 

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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 are also expected to continue to grow by 30%, a rate that’s faster than average.* 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 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 use Python and R to learn data processing algorithms, while other hands-on projects include exercises and assignments in Tableau, SAS Enterprise Miner, SAS Text Analytics, and SAS Visual Analytics. Our partnership with SAS and its heavy integration into the coursework helps you build proficiency that translates into a competitive advantage in the job market. As a graduate of the M.S. in Data Analytics program, you will also receive a SAS Tier 2 Academic Specialization in Data Analytics along with your master’s degree to recognize your achievement with SAS technologies. 

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. 

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

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Data Analytics Courses & Curriculum

32 Semester Hours
Course Sequence (32 hours)
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 (4)
This course examines the issues in management and analytical analysis of massive datasets, and unstructured data, including data warehousing from an enterprise perspective. Students will learn the concepts and techniques for managing the design, development, security and maintenance of enterprise information.
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 - Data Mining (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 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.

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Master's in Data Analytics Program Details

Tier 2 SAS Academic Specialization in Data Analytics

Earn a badge that designates you as a skilled analytics professional

As part of your Franklin master’s degree, you’ll also earn a SAS Tier 2 Academic Specialization in Data Analytics. According to EMSI labor market analytics, nearly 220,000 job postings listed SAS as a desired skill in 2019. This digital badge, issued jointly by SAS and Franklin University, recognizes your ability to leverage SAS analytic tools for data preparation, advanced analytics and visualization. The badge is awarded after your successful completion of three master’s-level courses: MATH 601 (Introduction to Analytics), DATA 605 (Data Visualization and Reporting) and DATA 610 (Big Data Analytics). The knowledge gained through these courses provides you with valuable insight that is sought by SAS customers at more than 65,000 sites in more than 135 countries, including 90 of the top 100 Fortune 500 companies. 

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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

34%

From 2018-2029 jobs in Data Analytics are expected to increase by 34%



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:

Data Analytics Frequently Asked Questions

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Investigate Your Options

Interested in a career that focuses on data and information, but not quite sure where you fit? 

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