Data Analytics

Information and Technology


10 Weeks


Ascend in the information age and make it routine. Interpret growing data by sifting and deriving meaning for insights to support the business.


This course provides an understanding of data analytics around topics such as data analytics techniques, types of data, business intelligence, data warehousing and advanced analytics such as predictive and prescriptive analytics. The course will allow you to acquire additional skills and tools, such as using MS Excel for data analysis and to understand where advanced analytics tools fit in, to prepare you for a career in the information age.

Subject Matter Expert

Dr Budree spent over a decade in the corporate world in various management roles for multinational organisations in information systems, data analytics, strategic planning and market insights and research. He has also consulted in both the public and private sectors in South Africa and abroad.

Dr Budree’s research areas are business intelligence, data analytics, ICT for development, e-commerce and design thinking. He has published in conferences and journals across the world. He currently chairs the E-commerce Forum Africa. Dr Budree has served as a guest lecturer, for Hochschule Neu-Ulm in Germany on their MBA programme, as well as for the postgraduate information systems programme in business intelligence and data analytics at the University of the Western Cape.

Course and Technical Requirements


To successfully access and complete this course, you will be required to have a registered email account, access to a computer/laptop/tablet and stable internet connection. You will be required to be familiar with using a computer as you may need to be able to read and download documents in Adobe PDF Reader, view Microsoft PowerPoint presentations, and read and create documents in Microsoft Word.


Our online short learning programmes may require additional software applications. These additional software applications requirements will be communicated to you in this information pack and/or on the website course page. UNi4 Online does not provide any additional software applications required for online short learning programmes.

Please note: Google, YouTube and Vimeo may be used in our online course delivery. If any of these services are blocked in your jurisdiction, you may have difficulty in accessing our course content

Learning Approach

Our online short learning programmes are broken into self-paced manageable modules designed to be interactive and engaging:

  • The programme is available to be viewed on smart devices and includes mobile, tablets and personal computers.
  • Relevant case studies, articles and recommended reading are part of supplementary resources available.
  • Apply and evaluate what you have learned in each module with the self-grading quizzes and assignment submissions.
  • View a range of introductory course videos by your Subject Matter Expert.
  • Scheduled live webinars are included with the Online Academic Tutor.
  • Network, collaborate and interact with your fellow participants and Online Academic Tutor via the discussion forum.


Upon successful completion of this online short learning programme, you will be awarded with a UNi4 Online Certificate of Completion.

Learning Objectives

Your dedicated Online Academic Tutor (OAT) will provide you with necessary guidance, offer advice and answer questions on course content, to help you achieve academic success.


  • MODULE 0 | Orientation Week 1
    Navigating the Virtual Learning Environment
  • MODULE 1 | What is Data Analytics? Week 2
    Key concepts, principles and components of data analytics
  • MODULE 2 | Introducing Business Intelligence (BI) Week 3
    Defining BI and looking at its role in business
  • MODULE 3 | Types of Data and Data Warehousing Week 4
    Components, principles and characteristics of data warehousing
  • MODULE 4 | OLAP (Online Analytical Processing) Week 5
    Implementing OLAP and data cubes
  • MODULE 5 | Levels of Data Analytics Week 6
    Distinguishing between reactive, proactive, prescriptive and predictive data analytics
  • MODULE 6 | Data Visualisation and Corporate Performance Management Week 7
    Explaining knowledge discovery and key concepts and principles of visual analytics
  • MODULE 7 | Basic Data Analytics in Excel Week 8
    Data analytics functionality of MS Excel and the role of pivot tables and charts in data analytics
  • MODULE 8 | Advanced Data Analytics Tools Week 9
    The use of data visualisation tools and the role of statistical analysis tools
  • MODULE 9 | Wrap-up Week 10
    Synthesise your learning journey experience

Payment options available to you

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