Postgraduate Diploma in Computer Software and Media Application

Purpose

This is a Postgraduate specialisation qualification that serves to consolidate and deepen the student's expertise in Software, Data Analysis and Logistics. It prepares individuals to design and manage the construction of databases and related software programmes and applications, including the linking of individual data sets to create complex searchable databases and the use of data in analytical search and design tools that includes formatting and extraction; data delivery; index design; implementation problems; planning and budgeting; and client and networking issues. Besides providing the students with a solid grounding in the academic theory underpinning the main concepts of the field of Information Technology, the curriculum includes a significant experiential component, culminating in an industry project, which forms part of the final assessment.

Rationale

The concept of Big Data has been around for years, it is only in the recent past that organisations have begun to realise and understand that they can productively utilise the volumes of information they have access to (and to use these data sets to) develop the required software and use it understand trends and insights. However, in order to optimize these insights, the analysis and interpretation of data in industries are required to create larger pools of skilled talent. Develop the necessary skilled human capital in the field of software development data analytics and business intelligence to fulfil in the talent shortage that is currently experienced in the South African market, to help ensure that the country can effectively compete in this area.

Recognition of Prior Learning (RPL)

Access to the qualification can also be provided in terms of the university's RPL policy and its admission criteria stipulated by Senate. The RPL process students have to undergo a Portfolio Development Course to support (PDC) the student's admission. The PDC will focus on written submission explaining the reasons for the candidates' interest in in the discipline as an adjunct to their existing professional competencies and indicating the nature of a possible research project. In addition, an application can be made in terms of rule A.2. The competency rule via Senate.

Entry Requirements

The minimum entry requirement for this qualification is

Bachelor's Degree with an average of 55% for exit level modules in the areas of Information Systems, Business Management, Computer Science or Statistics plus one of:

• Information Systems or Computer Science or Statistics at the 2nd year level.
• Bachelor's Degree (or equivalent) with two years relevant working experience.

Core Modules

• Decision-making in Business, Level 8, 15 Credits.
• Data Management, Level 8, 15 Credits.
• Data Warehousing and Data Structure, Level 8, 15 Credits.
• Research Project, Level 8, 30 Credits.
• Analytics and Business Intelligence, Level 8, 15 Credits.

Select 2 from

• Statistics and Visualisation, Level 8, 15 Credits.
• Introduction to Data Mining, Level 8, 15 Credits.

Or

• Fundamentals of E-logistics, Level 8, 15 Credits.
• Data and Decision making in Supply chain and logistics, Level 8, 15 Credits.

1. Analyse user's needs then designed, tested and developed software to meet these needs.
2. Create a variety of models and diagrams (flowcharts etc that guides programmers how to write the code).
3. Provide the broad understanding of master data management, i.e. the software strategies, process, tools, standards, definitions, and management of data for ease of use and reference within the organisation.
4. Design, develop and update business intelligence applications via software applications.
5. Visualise, analyse and interpret data using appropriate statistical techniques.
6. Use and apply business intelligence and analytics in solving identified business challenges.
7. Apply data-mining package to visualise and explore data patterns for basic predictive modelling.
8. Apply the theoretical knowledge in terms of the software development, structuring, managing and analytical manipulation of data via real-world projects in a public or private company.
9. Use and apply business intelligence and analytics in solving identified logistics business challenges.
10. Provide the broad understanding and master data management, i.e. the strategies, process, tools, standards, definitions, and management of data for ease of use and reference within logistics organisations.

Associated Assessment Criteria for Exit Level Outcomes

• Apply the design features and methodologies used to develop business computing software systems.
• Understanding of Network topologies, classifications and protocols.
• Apply network management tools correctly and efficiently.
• Provide example in ways in which the Information Technology (IT) environment can be management.
• Create a data an and information strategy.
• Understand the opportunities and constraints of working with data (incl. social media, online presence, crowdsourcing).
• Managing data and information projects.
• Understanding of big data and its management.
• Evaluate buying and building data management systems.
• Apply business intelligence applications.
• Summarize and visualise basic data into summary measures (e.g. mean, median, standard deviation, appropriate graphical displays).
• Use computer tools and techniques to analyse data.
• Apply key concepts around Business Intelligence.
• Apply types of data and software validation to test data and software reliability.
• Evaluate business data requirements.
• Engage with clients to define and scope the business need/challenge and/or opportunity.
• Correctly analyse problems, confirmation and feedback documents from the organisation are presented and documented as a research project.

Integrated Assessment

The University adopted a Continuous Assessment System. Assessments consist of number assessment events throughout the year and a variety of assessment instruments are used (for example, tests, essays, practical reports, project reports and oral presentations).

The qualification presents opportunities for practical experience in each of the modules and these experiences are integrated in the research project. The research project will be executed and implemented within the "world of work"/business context which will facilitate the integration and application of the theoretical knowledge in a hands-on manner in a real-world situation.