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OCU’s Data Analytics major prepares students for a career in data analytics within the information technology area. Through this major, students define challenges in providing useful data acquired from multiple sources and resolving cross-organizational problems through analytics.


On completion of the major, students should be able to:
  • Identify the various analyses available from different data sets.
  • Communicate various aspects of analysis to IT and non-IT stakeholders.
  • Evaluate ethical issues in data analysis.
  • Integrate Christian principles in critical thinking and decision-making.
  • Apply management principles to work with people and processes within an organization.
This degree program is available in the following formats:

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100% Online courses in a 5-week as-you-go flexible format for busy adults featuring forum discussions and weekly assignment deadlines.


  • The double-entry system of bookkeeping and the basic accounting cycle, including communicating financial information according to generally accepted accounting principles.
    Prerequisite: College-level mathematics courses, higher than MAT1000
  • Introduction to economic analysis at the aggregate level, including the impact of both domestic and international policies on key economic indicators and on overall macroeconomic performance. Recommended: College-level economics course
  • Principles and practices of law, and their impact on business situations, emphasizing the dynamic interaction between the individual, organization, and society, in the context of Christian ethics and proper business conduct.
  • Computer hardware, software, and operating systems, including operating system configuration and maintenance, client systems, managing applications, networking concepts, and skills for a career in network support or administration.
  • Application of skills and knowledge required for a career in network support or administration.
    Prerequisite: IST2000
  • The Windows operating system, including practical skills in installing, configuring, and maintaining this operating system, and an introduction to other popular operating systems, including OS X, iOS, Android, and Linux.
  • Relational databases, including basic relational database design and maintenance, design concepts such as records, tables, data types and table normalization, reading database data through queries using query functions and linked tables, an introduction to the SQL query language, popular relational database software, alternate database technologies, and interaction with these concepts using a relational database software program.
  • An introductory course in computer programming using the JAVA programming language, including the fundamentals of computer programming, program design, data types, program flow constructs, efficient program design, and techniques for processing data programmatically such as data arrays and data algorithms.
  • The effect of human factors on technology systems, including the social and organizational impact of technology and understanding the user experience in relation to individual and group application of technology.
  • Fundamental concepts and technologies for business information systems, including data capture, processing, and communication, introduction to the integration of Microsoft Excel and Microsoft Access in business information systems, and basic data analytics.
  • Techniques and tools for analyzing large data sets.
  • Information systems security, including security for networks, applications, data, and host computers, compliance, operation security, access control, identity management, threats and vulnerabilities, and cryptography.
    Prerequisites: IST2000, IST2010
  • Hands-on interaction with the MySQL database, including skills required to install, configure, secure and maintain an enterprise database system, designing and creating a simple database, and interacting with the database through applications and programming languages.
    Prerequisite: IST2400
  • Programing for the World Wide Web, including web page definition, scripting languages (HTML, Javascript), complex web pages, use of scripting to enhance web pages, mobile friendly web pages, automated web page creation tools, and the appropriate use of these tools.
    Prerequisite: IST2500
  • Principles and solutions for managing IT projects through all phases, including initiation, planning, executing, monitoring and controlling, and closing.
  • Application of data management principles from Data Analytics I to solving business problems.
    Prerequisite: IST3100
  • Application of the System Development Life Cycle (SDLC) framework to plan, analyze, design, implement, and maintain information technology systems, including methods and models for developing and documenting the requirements for an information system, processes and procedures to design, procure, implement, and maintain systems, and an introduction to industry standard methods and tools that support the SDLC process such as UML, Use Case analysis, Rapid Application Development and CASE.
  • Ethical and legal issues in the use of the Internet, with emphasis on privacy, intellectual property, freedom of expression, and e-commerce.
  • Decisions and activities required to implement an information system project, emphasizing strategic decisions based on technical, business, political and legal factors, vendor selection, relationship management, and human factors such as change management, education and training.
  • Practical experience using the SQL language to write various queries to extract meaningful data from a relational database.
  • Integration of student learning from the Data Analytics major courses requiring the application of learned skills in analyzing data, making predictions, and identifying, evaluating, and capturing business analytic opportunities that create value.
    Prerequisite: Completion of major courses
  • Statistics is the method of conducting a study about a topic by collecting, organizing, interpreting, and presenting data. This course prepares the student to perform statistical analysis of data sets. Topics include descriptive statistics, probability, sampling distributions, interval estimation, hypothesis testing and regression.

*Students may count this course as a Mathematics elective in the General Education Core.

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