Undergraduate Concentration in Business Analytics

Organizations make smarter decisions when they effectively harness the power of data. The business analytics concentration is designed to provide the analytical skills, techniques, and perspectives required to understand, analyze, and interpret datasets of various sizes and content. This knowledge and skill set can be used to help companies improve decision making in increasingly complex and interconnected business environments and create measurable improvements in business performance.

This concentration offers courses that cover the fundamentals of data analysis and management, information visualization, and descriptive, predictive, and prescriptive analytic techniques. These techniques are often based on artificial intelligence, machine learning, and data mining. Courses are grounded in relevant theory and principles, but also explore how to apply these concepts to investigate realistic datasets by using a variety of innovative computational tools and programming languages. These may include Python, R, SQL, and Tableau. Students can develop technical and problem-solving skills that are in high demand by employers and can apply those skills through both classroom activities and co-ops focused on business analytics.

Analytics can be employed in many different parts of an organization. Therefore, students are encouraged to consider completing a dual concentration in business analytics and another area. Graduates of this program have a wide range of career paths to suit their interests. Professional options include business or information analyst, consultant, and project manager. Graduates may also become specialists within a specific department or functional area, such as financial services, accounting, marketing, or manufacturing.

Business Analytics Curriculum Details

Find the full set of Business Analytics concentration requirements in Northeastern's Course Catalog. Concentrations complement the business degree programs and combined majors offered.

Upper-level students: Please consult the Course Catalog appropriate to your class year and your academic advisor to ensure your coursework is on track.

Required Courses

MISM 2510. Fundamentals of Information Analytics. (4 Hours)

Focuses on information analytics concepts and techniques needed by educated information analysts, designers, and consumers to lead organizations in the contemporary information age. Includes concepts, techniques, methods, and strategies for the entire information life cycle—collection, organization, exploration, analysis, manipulation, visualization, interpretation, and presentation of information for business. Each of these topics is introduced with real-world examples and data sets, grounded in relevant theory and principles, and is reinforced using various user-friendly software tools to gain the necessary analytical skills and knowledge.

MISM 3403. Data Management in the Enterprise. (4 Hours)

Offers students an introduction to and overview of the methodological frameworks and tool sets for the design, development, and implementation of data-management solutions. Today, almost no aspect of business operates without a strong reliance on the flow of information. Even small enterprises track huge volumes of data, from sales transactions and supply chain activities to Web site traffic. Knowledge workers and managers at all levels within the organization require an understanding of data management, database design and operations, and associated decision-support and data-analysis tools and systems to complete even day-to-day tasks. Offers students an opportunity to work hands-on, applying these methods and tools to solve actual business problems. Prerequisite(s): (ENGL 1111 with a minimum grade of C or ENGL 1102 with a minimum grade of C or ENGW 1111 with a minimum grade of C or ENGW 1102 with a minimum grade of C)

– OR –

MISM 3405. Data Wrangling for Business Analytics. (4 Hours)

Covers data wrangling principles and novel techniques for business analytics. Key topics include data profiling, data retrieval, data cleansing, and data integration, as well as data extraction and exploration via APIs. Applies the principles of data wrangling for structured and unstructured data using industry tools such as Oracle, SQL, statistical programming languages (R/Python), and visualization tools (Tableau). Offers students an opportunity to learn data wrangling techniques to identify and solve real-world data challenges, creating business value from the vast amount and types of traditional and big data.

MISM 3501. Information Visualization for Business. (4 Hours)

Introduces the use of design, interaction, and visualization techniques and strategies to support the effective presentation and manipulation of business information. Based on principles from art, design, psychology, and information science, offers students opportunities to learn how to successfully choose appropriate methods of representing various kinds of business data to support analysis, decision making, and communication to organizational stakeholders.