At its core, the role of the data analyst is to comb through facts, statistics and other raw data gathered from various sources to build a holistic view of the scenario which they have been tasked to model. This scenario provides the basis for further insights and analysis, in order to propose various solutions to the given challenges, and predicting their likely outcomes, thus aiding the company in developing effective strategies.

This eventual output involves a myriad steps and competencies. You will produce and track key performance indicators and work with IT teams, management and data scientists to determine organizational goals. Once you have established your goals, you will be responsible for developing records management processes and policies, setting up and maintaining automated data processes, as well as gathering, understanding and documenting detailed business requirements using appropriate tools and techniques.

You will mine data from primary and secondary sources, analysing large datasets to draw valid inferences. Data quality must be audited and maintained, through efficient automation processes. Tools to support data validation and cleansing must be developed in order to retain only relevant information.

Once the data is gathered and qualified, you will develop and support reporting processes. You will liaise with internal and external clients to fully understand data content while manipulating, analysing and interpreting complex data sets relating to your employer’s business, using statistical tools and techniques.

Your learnings must then be represented in reports for internal and external audiences using business analytics reporting tools, data dashboards, graphs and visualisations. You will provide sector and competitor benchmarking, pinpoint trends, correlations and patterns, and provide concise data reports and clear data visualisations for management.

All the while, you will be improving processes by designing, creating and maintaining relational databases and data systems and working through code problems and data-related issues, all to ensure the most accurate information is available, and that the most valuable insights and strategies are presented to management.

• Data Analyst
• Business Intelligence Analyst
• Credit Analyst/Manager
• BIBA
• Functional Analyst

• Data Analyst
• Business Intelligence Analyst
• Credit Analyst/Manager
• BIBA
• Functional Analyst

You can study any of the following degrees:

• Business Information Systems
• Computer science
• Economics
• Information Management
• Mathematics
• Statistics

• School of Information Technology and Data Science
• University of Cape Town
• Monash
• University of Pretoria
• University of Venda
• University of Fort Hare
• Wits University
• Rhodes
• University of Stellenbosch
• University of Johannesburg
• Nelson Mandela Metropolitan University
• UNISA
• University of North-West
• University of KwaZulu-Natal
• Varsity College

These degrees are geared towards developing skills and knowledge that are vital to success in this field.

Should you choose to focus on Mathematics, you will learn numerical and analytical skills, applied Mathematics , Mathematical and risk modelling, statistical methodologies and data analysis techniques.

For the technologically inclined, you will learn about VBA and SQL Servers, APIs, and XML. Business intelligence and analytics platforms are key, as are statistical programmes. Programming languages such as R, Python and MATLAB will provide a basis for data gathering and analytics.

Finally, if finance catches your interest, you will develop your knowledge of accounting procedures and financial reporting practices, financial modelling, and your knowledge of economics in order to analyse current economic condition and predictions for future economic indicators.

It is important to note that data analysis is not a purely scientific field. A data analyst needs to be able to properly communicate with internal and external stakeholders to inform their analysis, and present complicated scientific and technical findings in a way that makes sense to laymen. As such, a data analyst needs an excellent command over English and strong conversational skills. It also requires the ability to present findings in easy-to-consume reports and presentations. They need strong organisational and co-ordination ability, patience and an ability to spend long periods of time working on their own, trawling through code and spreadsheets on a computer screen. A data analyst employs best practice techniques to analyse large amounts of data whilst maintaining intense attention to detail. They require a deep understanding of the industry, of current data collection and analysis techniques, as well as the ability to question existing practice and develop new practices.