Master of Science in Business Systems and Analytics Online

Strengthen your business decision-making and problem-solving leadership capabilities with the latest data analysis and application knowledge and technology skills.

Apply by: 5/8/23
Start classes: 5/22/23
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Program Overview

Explore the online M.S. in Business Systems and Analytics program

Total Tuition: $25,500
Program Duration: As few as 14 months
Credit Hours: 30

Advance to leadership roles with crucial business analytics and data science knowledge and experience. The globally competitive marketplace in today’s information age requires professionals with specialized knowledge and experience. Organizational, technology and analytical skills, combined with creative thinking, problem-solving and effective communication, are critical.

The STEM-designated Master of Science in Business Systems and Analytics online at La Salle University offers an in-depth, comprehensive immersion in the transformation of data into insights that better inform business decision-making. As a graduate of this master’s in business systems and analytics program, you will possess a thorough understanding of how business leaders can combine statistics, operations research and information systems to drive growth and productivity.

Graduates of the online M.S. in Business Systems and Analytics program will learn how to:

  • Understand and apply the fundamental concepts of business systems and analytics
  • Use analytic methods and information systems tools and technologies to drive effective, data-supported initiatives and solutions across varied business areas, including finance, accounting, marketing and supply chain management
  • Identify, formulate and solve optimization problems and perform sensitivity analysis and simulation to examine alternative scenarios
  • Effectively communicate the results of analytic solutions to business problems and decisions using appropriate data visualization
  • Understand and apply the fundamental concepts of business systems and analytics
  • Use analytic methods and information systems tools and technologies to drive effective, data-supported initiatives and solutions across varied business areas, including finance, accounting, marketing and supply chain management
  • Identify, formulate and solve optimization problems and perform sensitivity analysis and simulation to examine alternative scenarios
  • Effectively communicate the results of analytic solutions to business problems and decisions using appropriate data visualization

Upon completion of the online M.S. in Business Systems and Analytics, you will be prepared for a wide range of roles, including:

  • Business Intelligence Analyst
  • Data Mining Analyst
  • Operations Research Analyst
  • Business Intelligence Analyst
  • Data Mining Analyst
  • Operations Research Analyst

Online business programs also available:

La Salle University offers a variety of specialized business programs. Check out all of our business online programs.

Total Tuition: $25,500*
Program Duration: As few as 14 months
Credit Hours: 30

Accreditation:

AACSB accredited logo

The La Salle University School of Business is accredited by AACSB International (AACSB). Less than 6 percent of the world's schools offering business degree programs hold AACSB business accreditation.

Need More Information?

Call 844-466-5587

Call 844-466-5587

Tuition

Discover how to pay for this online master’s degree

Our Master of Science in Business Systems and Analytics online program offers affordable, pay-by-the-course tuition which is the same for in-state and out-of-state students. All program and course fees are included in the total tuition cost.

Tuition breakdown:

Total Tuition: $25,500
Per Credit Hour: $850

Tuition breakdown:

Total Tuition: $25,500*
Per Credit Hour: $850

Calendar

Familiarize yourself with the dates and deadlines you need to know

La Salle University online programs are delivered in an accelerated format ideal for working professionals, conveniently featuring multiple start dates each year.

Now enrolling:

Next Apply Date: 5/8/23
Next Class Start Date: 5/22/23
TermStart DateApp DeadlineDocument DeadlineRegistration DeadlineTuition DeadlineClass End DateTerm Length
Summer 15/22/235/8/235/12/235/17/235/18/237/16/238 weeks
Fall 18/28/238/14/238/18/238/23/238/24/2310/22/238 weeks
Fall 210/23/2310/9/2310/13/2310/18/2310/19/2312/17/238 weeks

Now enrolling:

Next Apply Date: 5/8/23
Next Class Start Date: 5/22/23

Have questions or need more information about our online programs?

Ready to take the rewarding path toward earning your degree online?

Admissions

Make sure you meet the requirements for our business systems and analytics master’s program

Applications for the Master of Science in Business Systems and Analytics are evaluated on a holistic basis. The Admissions Committee takes into account interest, aptitude and potential for achievement in graduate studies. The requirements include:

Admission Requirements:

  • Bachelor’s degree from an accredited institution
  • Minimum 3.0 GPA
  • GMAT waiver available

Prior to evaluation by the Admissions Committee, applicants must submit the following:

  • Transcript(s) from the college/university where you earned your bachelor’s degree and, if applicable, master’s degree. You will be notified if you need to submit additional transcripts for advising purposes.
  • Minimum 3.0 GPA
  • GMAT waiver available

Documentation can be sent via email to [email protected]. If you need to submit official documents by mail, send them to:

La Salle University
Office of Adult Enrollment
Box 112
1900 West Olney Avenue
Philadelphia, PA 19141

Have a question? Call us at 844-466-5587.

Courses

Take a look at the curriculum for this degree program

For the M.S. in Business Systems and Analytics online, the curriculum is comprised of 10 courses (30 credit hours )—depending on prior academic and professional experience.

Duration: 8 weeks
Credit Hours: 3
This course introduces students to the growing field of business analytics. Business analytics is the use of data, information technology, statistical analysis, and quantitative methods and models to support effective organizational problem solving and informed decision making. The course includes methods, tools and techniques for summarizing and visualizing historical data, which is relevant to descriptive analytics–the use of data to find out what has happened in the past or is currently happening; methods, tools and techniques for extracting information from existing data in order to determine patterns, which is relevant to predictive analytics–the use of data to find out what will happen in the future; and methods, tools and techniques for optimization, which is relevant to prescriptive analytics - the use of data to determine the best course of action in the future. Prerequisite: MBA 601, MBA 602 or equivalent course work.
Duration: 8 weeks
Credit Hours: 3
This course focuses on data warehousing and data mining in organizations. Topics covered in the course include: data warehousing and mediation techniques aimed at integrating distributed, heterogeneous data sources; data mining techniques such as rule-based learning, decision trees, association rule mining, and statistical analysis for discovery of patterns in the integrated data; and evaluation and interpretation of the mined patterns using visualization techniques. Prerequisite: MBA 693.
Duration: 8 weeks
Credit Hours: 3
This course introduces today's most valuable marketing research and analytics methods and tools and offers a best-practice methodology for successful implementation. Hands on projects and case studies provide students an opportunity to apply the marketing research and analytics techniques for solving key problems, ranging from product development, segmentation, pricing, campaign management, brand valuation, and digital marketing strategy. Prerequisite: MBA 690.
Duration: 8 weeks
Credit Hours: 3
This course is built from the premise that technology has changed the role of the accountant. A heightened awareness of systems, technology, and data analysis is becoming increasingly required of individuals in the different accounting fields. Data has proliferated in business, and managers and accountants need to understand the implications for decision-making and tap into the data to provide better insights into a firm/client/customer/supplier, etc. This course is intended to provide students with an understanding of data analytic thinking and terminology as well as hands-on experience with data analytics tools and techniques. Students should leave this course with the skills necessary to translate accounting and business problems into actionable proposals that they can competently present to managers and data scientists. While there will be some use of tools in this course, the focus of this class is on concepts, not algorithms or statistical math.
Duration: 8 weeks
Credit Hours: 3
This course is about the manager's responsibilities for problem solving and decision making, and those areas in which information technology can be used to gain the insight needed to support selection of decision alternatives. Students learn about the role of data, information and knowledge in managerial problem solving and decision making. Transactional processing and database management systems (DBMS) are used to store, manage and retrieve data in organizations. Decision support system (DSS) tools and technologies (such as natural language programming and influence diagramming) are used to organize data into information for decision analytics. Expert systems (ES) are used to synthesize information into knowledge for knowledge management. Students are required to use DBMS, DSS and ES software packages in a hands-on environment.
Duration: 8 weeks
Credit Hours: 3
One of the skills that characterize great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. In this course, students will learn how to visualize data, tell a story, and explore data by reviewing the core principles of data visualizing and dashboarding. The course aims to focus on effective and high impact visualizations of common data analyses to help them convey conclusions directly and clearly. Students will be able to get practice in designing and persuasively presenting business “data stories” that use these visualizations, helping stakeholders make decisions and take action based on their business data capitalizing on design principles.
Duration: 8 weeks
Credit Hours: 3
This course covers a broad overview of finance topics from a data analytics perspective. Students will learn the ins and outs of applied data analysis and a conceptual framework for thinking about data from both a statistical and machine-learning perspective with applications in finance. Students will learn to understand and apply concepts like capturing and analyzing new sources of financial data, building predictive models, and running simulations of market events, using concepts of data analysis and probability in investment science, risk management, valuations, rates of return and profitability analysis. The course aims to provide a theoretical and practical framework in which students will be challenged to solve real-world problems in the finance field and gain familiarity with commonly used stochastic models.
Duration: 8 weeks
Credit Hours: 3
This course is about structured analysis and design methodology for complex business systems. Students become familiar and use Entity Relationship Diagram, Data Structure Diagram, Data Flow Diagram, Data Dictionary, and Process Specifications to develop Systems Specifications. These specifications are utilized as the blueprint to develop and implement relational databases and explore the Structured Query Language (SQL) used to manipulate and operate the database. Prerequisite: MBA 693.
Duration: 8 weeks
Credit Hours: 3
This course is designed to introduce students to the principles of business application programming for business analytics using selected high-level languages such as R, Python, and Hadoop. Emphasis is placed on identifying the capabilities and limitations of statistical computing languages for big data. Students will learn skills and techniques to solve big data problems through a series of steps that involve identification of problems, design of the solution logic, formal representation of program specifications, and implementation. The focus is on accessing data from multiple sources, manipulating different types of programming objects, performing character manipulation, and generating reports. Students will design and develop several computer programs throughout the term.
Duration: 8 weeks
Credit Hours: 3
This course introduces students to decision making and problem solving with simulation and optimization tools and techniques. Students learn to formulate and construct a decision model with spreadsheets and use the optimization tools, Monte Carlo simulation, and sensitivity analysis to generate and interpret solutions. The course covers different types of optimization and simulation models, including linear programming, sensitivity analysis, integer linear programming, goal programming, multiple objective optimization, simulation modeling, and queuing theory.
Duration: 8 weeks
Credit Hours: 2
Financial Accounting: This course is an introductory study of financial accounting. This includes studying basic accounting language and concepts, recording financial transactions, and preparing and interpreting financial statements. Reporting and analyzing operating income, operating assets, and owner financing is also emphasized.
Duration: 8 weeks
Credit Hours: 2
This course serves as an introduction to the financial system and its relationship to domestic and international business activity financing. Financial market components and phenomena such as financial instruments, institutions, the flow of funds, market efficiency, interest rate determination and term structure, exchange rates, and government policy are analyzed. An introduction is given to the concept of financial asset valuation and the time value of money.

La Salle University is ranked in the top 50 percent of national universities nationwide by U.S. News & World Report (2023).

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