Part 3 of 9

In this blog, we’re unpacking the Data Analyst role. Sometimes referred to as “data scientists in training”, these analysts are usually limited to tackling specific business tasks using existing data sets, tools and systems, rather than being given the authority to create their own projects.

Data Analyst is an umbrella term that in many cases doubles for a variety of other job titles, including Marketing Analysts, Quantitative Analysts, Business Analysts, Data Warehouse Analysts or Business Systems Analysts.

Role Overview

Data Analysts are required to discover, through the collection, processing and statistical analysis of data, how data can be used to answer questions and solve problems. The complexity of the environment and the skill and experience of the individual would determine the scope of role. Their key areas of responsibility typically include:

  • Mining data from primary and secondary sources

  • Cleaning data to discard irrelevant information

  • Analysing and interpreting results using standard tools and techniques

  • Pinpointing trends, patterns and correlations in complicated data sets

  • Identifying new opportunities for process improvement

  • Presenting data reports and clear data visualization for management to make more effective decisions

  • Designing, creating and maintaining relational databases and data systems

  • Working with IT teams and management to determine organisational goals and monitoring metrics


Due to the analytical nature of this job, most individuals at entry level are required to hold a degree in mathematics, information management or economics. In each instance, the degree should carry subjects with a heavy emphasis on statistical and analytical skills.


Analytical Problem-solving

Employing best practice to analyse large amounts of data whilst maintaining intense attention to detail.

Technical Skills

In a dynamic environment such as this, technical skill competence can change rapidly, and this therefore serves as a guideline.

  • Statistical methods and packages (e.g. SPSS)

  • R and/or SAS languages

  • Data warehousing and business intelligence platforms

  • SQL databases and database querying languages

  • Programming (e.g. XML, Javascript or ETL frameworks)

  • Database design

  • Data mining

  • Data cleaning and munging

  • Data visualization and reporting techniques

  • Working knowledge of Hadoop & MapReduce

  • Machine learning techniques

Effective Communication

Ability to translate technical concepts into pragmatic solutions that management, and other staff members, understand and can buy-into.

Creative Thinking

Willingness and ability to question established business practices and lead brainstorming for new approaches to data analysis.

Industry Knowledge

Knowledge and understanding of what drives business in the chosen sector/industry and how effective analysis of key data can contribute to the success of the company’s strategy.

Career Pathway

Depending on the environment, the Data Analyst may have a range of career options available, most obviously promotion to Data Scientist. For those analysts who grow weary of number crunching, there may be avenues to shift into data construction roles such as Data Engineer, Data Architect or Hadoop Developer, for example.

Remuneration Trends

Remuneration is directly linked to job responsibilities. A senior Data Analyst with the skills of a Data Scientist can command a high price, particularly in today’s skills-short market. The addition of technical skills, including additional programmes and languages, can improve earnings potential. At entry-level, Data Analysts would be earning R200k per annum with those carrying greater levels of experience and skill as much as R600k per annum.

Outlook: Future of Work

Change is already here with increasing numbers of self-service business intelligence software becoming available to operations and management teams. These systems now automate many of the regular tasks that previously would have been required to be completed by Data Analysts.

Today, many managers and operational individuals can, at the touch of a button, generate data reports, build dashboards and monitor numbers to assist them in managing their desks or departments in real-time. As a result, the need for analysts to extract information and prepare it into a readable format is rapidly decreasing.

The rapid rise in sheer volume of data, especially that in unstructured formats (such as from social media feeds) means that Data Analysts are required to clean, filer and convert billions of diverse data points. To do this, they are expected to employ complex modelling and predictive analytics techniques to generate useful insights and actions and then to explain to their colleagues, in laymen’s terms, how this can be used to the benefit of the business. In a nutshell, Data Analysts need to acquire the skills to perform as Data Scientists.

Our Data & Analytics Expertise

Look out for the other installments in this 9-part series, where we unpack each of the 8 core roles within the Data & Analytics environment. Visit to view our blog and make sure you follow us on our TSR social media platforms to access each part in the series.

If you’re looking for an opportunity within the Data & Analytics space and would like to have a confidential career conversation, please get in touch with our expert recruiter, Sheila Mtakwa ( And if you’re looking to enhance your organisation’s data or analytical capability, look no further. We’d be delighted to meet with you for a no-obligation consultation on how to boost your chances of securing the best talent available in the market.