Master of Science in Information SystemsBusiness Analytics Track

  • Starts in the fall (August) at the Modesto Maidique Campus
  • Meets Saturdays from 8:30 a.m. to 5:30 p.m.
  • Hybrid format (on-campus and online)
  • 14 months

With a partnership with business communities, the MSIS business analytics track is designed to provide advanced analytical skills and knowledge in big data and quantitative analysis. Students focus on a unique combination of analytical and information systems management skills that will make them experts in guiding businesses in improving processes, products, services and software through data analysis

Place yourself in the perfect spot between IT and the business administration to help bridge the gap and improve efficiency.


The Master of Science in Information Systems offers an innovative curriculum that best prepares students to meet the emerging industry needs and challenges. Students are recommended to have minimum knowledge in the following areas:

  • Introductory level programming languages
  • HTML
  • Introduction to databases
  • Microsoft Office

If you do not have a programming background, you are strongly encouraged to gain some familiarity with an object-oriented programming language (e.g., Java or Visual Basic) before beginning this program.

Websites like and offer resources to further assist.

Core Courses

In the recent years, businesses have witnessed an unprecedented surge of data generated from various channels such as smart devices and social media. Increasingly, modern businesses are recognizing the need for “data science” skills for leveraging such data to derive insights and improve outcomes. As an interdisciplinary field, data science draws from a broad range of skills such as machine learning, natural language processing and cloud computing to effectively collect, store, and process large amounts of data. This course will provide an understanding of fundamental data science concepts and techniques needed in today’s distributed information systems’ environment.

Software: Rapidminer, IBM’s Hyperledger Composer, and IDLE

This course examines the defining characteristics of IT projects and introduces a variety of relevant techniques. The course includes project manager functions like managing scope, time, quality, and cost.  Students will learn about project management methodologies such as the AGILE method.

Software: Microsoft Project 2016

This course focuses on the fundamental concepts, frameworks and techniques that can be used to analyze and redesign business processes through strategic and operational mappings and alignment between strategy, process and technology. The course covers how to map strategy, process and technology and how to conduct business process as-is and to-be, analysis and design.

Software: Microsoft Visio, LucidChart, IBM Process Integration Modeler

This course will help students critically think about how to conceptualize and model databases, and use query languages to manipulate databases to obtain information that can help a manager make decisions. The course takes a transaction-based (OLTP), data-oriented view that is embedded in the larger processing view. The course is primarily driven by problem-solving exercises and case discussions in a collaborative environment. Students should be able to extend their learning to unfamiliar environments and applications, and to communicate their knowledge.

Software: SQL, Visio, Lucidchart, Access, Neo4j, Tera

This course will introduce students to the field of Systems Analysis and Design in general, and focus in depth on object-oriented concepts, methodologies, models and skills, along with associated software tools. In this course, we will consider the case where custom software is required to solve a business problem or automate a business process. To this end, we will consider the major object oriented methodologies, and follow a lightweight version of the Rational Unified Process in case study form. All of these methodologies require a consistent means of describing various dimensions of a software design. The Unified Modeling Language (UML) provides an industry-accepted standard graphical language for describing different aspects of a software system. We will cover some of the major parts of the UML in this class.

Software: Unified Modeling Language (UML)

This course focuses on the managerial aspects of information security. Topics covered include access control models, information security governance, and information security program assessment and metrics. Coverage on the foundational and technical components of information security is included to reinforce key concepts.

Software: Wireshark, Webgoat, Security Onion

The focus of this course includes: 1) The top management's strategic perspective for aligning competitive strategy, core competencies, and information systems (IS); 2) The development and implementation of IS strategic plans to achieve organizational goals; 3)  Frameworks for creating IS value; and 4) Methodologies for designing the IS organization in accordance with IS governance best practices.

Students develop an understanding of the strategic use of IS from a business perspective at the enterprise level. They are expected to understand the competitive environment from the point of view of the CIO and to examine strategies and tactics available to use information systems for competitive advantage. Students will also understand how to define and implement IS governance to enable both business and IS executives to execute their responsibilities, in support of business/IS alignment and value creation.

Seminars will focus on soft skills such as leadership, team building, oral presentation, and career exploration. There will be team-building activities which include classroom exercises in group decision-making and problem-solving. Challenging group exercises will be included to help participants build the skills they will need to work together in the program and to succeed in today's team-based organizations. Students will also work with a presentation skills coach to improve their communication skills which are critical to managerial success.

The program will also offer a series of technical seminars including R, Python, Excel, and Access/SQL to build a foundation for the courses in the program, as well as provide students with a chance to explore some areas more in depth.

All Professional Development Seminars are mandatory.

Analytics Track

This course will introduce students to the relevant quantitative techniques required for business analysis and decision making, including decision models, mathematical programming, statistics and forecasting. Students will learn about the use of quantitative methods for turning data into information and information into good business decisions for managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, this course introduces students to the important role that data plays in understanding business outcomes and improving business processes.

Software: Excel, SAS, Rapidminer

In this course, students will design and implement an enterprise data warehouse architecture, utilize ETL tools and techniques to load data into the data warehouse, build and deploy multi-dimensional cubes, and utilize powerful reporting tools to analyze large volumes of data and convert these data to useful information. Using powerful data visualization tools, students will learn how to use data to explain the past, monitor the present, and anticipate the future.

Software: SQL Server RDBMS, SQL Server Analysis Services, SQL Server Data Tools, Tableau reporting software, Power BI, Python scripting

This course focuses on data mining techniques used specifically for business problems. Topics student will cover include: Overview of data mining; supervised data mining techniques: customer/employee churn, targeted mailing, fraud detection; unsupervised techniques: customer profiling.

Software: Excel, Rapidminer, R, Python

This course focuses on data visualization techniques with structured and unstructured data. Topics include: overview of data visualization, understanding dimensions and measures, data wrangling and blending, formulating practical research questions, matching questions with basic/advanced chart types, calculation and parameter, creating dashboards and stories, and dashboard critics

Software: Excel, Tableau Prep (Data Wrangling Tool), Tableau Desktop with R integration

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