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Short Course
Unstructured Data and Big Data
The financial and other industries currently have a shortage of people with the necessary data science skills to address problems relating to large and/or complex data sets. Nowadays financial institutions are confronted with an abundance of data, and so in order to maintain a competitive advantage, it is imperative to have analysts with these necessary data science skills. This short course will address one of the topics needed to become a skillful data scientist.

Purpose of the course:

This short course aims to equip participants with the skills necessary to use large volumes of unstructured data in applications for data analysis. This includes the storing and manipulation thereof and an understanding of the capturing and storage of diverse large data sets.

Admission requirements:

Admission requirements: 
NQF level 7 majoring in either Mathematics/Statistics/Engineering/Computer Science.
Learning assumed to be in place: 
NQF level 7.

Course outcomes and assessment criteria :

Course outcomes and the associated assessment criteria: 

Study Unit


Assessment Criteria

  After completion of this course, participants will: Participant will be assessed on the following criteria:
  1. Demonstrate applied knowledge and understanding of the nature and architecture of unstructured databases and understand how it is applied in practice. 
  2. Demonstrate an ability to identify real-world practical problems that can be solved using analysis of large quantities of diverse data and then apply data manipulation and query methods to solve these problems. 
  3. Demonstrate an ability to use a range of data manipulation and query skills to identify, analyse and address complex problems. 
  1. Explain the characteristics of unstructured data
  2. Critically discuss the capture and storage of unstructured data
  3. Use tools to analyse and report on unstructured data
  4. Use tools to manipulate unstructured data
  5. Implement a solution to a business problem using a large unstructured data set.


Assignments and participation.
Method of assessment: 
Learning objectives will be accomplished through the successful completion of assignments and participation in short course activities, proving insight into the topics at hand.

Additional information

Mode of delivery: 
Target group: 
Graduates and/or industry professionals working in fields that require data science and analytical skills.
Contact us
Prof Roelien Goede
Telephone number: 
018 285 2670