Data Analytics

Overview

With a heavy focus on real-world learning experiences, the program will build competencies in you for extracting deep insights from big data that are readily applicable in a range of contexts and industries.

The M.S. program in Data Analytics at Northern Illinois University provides students the advanced knowledge and skills to analyze organizational data. The use of analytics is accelerating due to technological advancements, exponential growth in data, and increasingly sophisticated application by organizations. Analytics is embedded in all industries, business functions, and employee workflows. The program prepares students for data-driven leadership and problem solving. Graduates of the M.S. in data analytics will be data-driven thinkers to approach business decision-making more rigorously and confidently, while effectively communicating data findings, interpreting complex data, and guiding their organizations in making more informed and actionable strategic decisions.

The program is in an online format for a large population of potential graduate students who cannot commit to either a full-time or location-based program to obtain the advanced degree. The program consists of two phases. Phase One (6 semester hours) is designed to address deficiencies in undergraduate course work considered to be prerequisite for the Phase Two (30 semester hours) graduate course work. Students with significant undergraduate course work in business may be waived from some, or all, of the Phase One requirements. Exemption exams are also available to waive Phase One requirements. There is no charge for the exam, however, a student may only attempt each exam once. Phase Two consists of 10 courses to ensure an in-depth study in data analytics.

Learning Outcomes

Learning Outcome 1: Demonstrate Data-Driven Problem Solving and Decision Making Skills

1.1  Demonstrate how analyzing data can improve decisions throughout an organization’s value chain.

1.2  Research and evaluate emerging technologies and data analytics trends in order to develop innovative data-driven organizational strategies and solutions.

Learning Outcome 2: Demonstrate the Ability to Access, Collect, Integrate, and Analyze Data in Order to Solve Business Problems

2.1 Differentiate different forms of analytics and the methods used in each.

2.2 Prepare data for statistical analysis.

2.3 Use analytical tools and software widely used in practice.

2.4 Perform basic exploratory and descriptive analysis, as well as predictive and prescriptive analyses.

2.5 Explain complex analytical models.

Learing Outcome 3: Demonstrate Business Communication and Presentation Skills

3.1 Effectively present results using data visualization tools.

3.2 Communicate and present complex analytics results to business clients, using practical and simple business terms that can be understood by general non-technical audiences.

Learning Outcome 4: Demonstrate Project Management and Critical Thinking Skills

4.1 Manage a data analytics project to interpret complex data and to guide their organizations in making more informed and actionable decisions.

4.2 Analyze critical factors leading to the identification of a business problem or opportunity. This may also lead to smarter business moves, more efficient operations, higher profits, and happier customers.