Posts by Dr. Jan van Niekerk

In the first part of this series, we looked at how the fears of technological innovation are resulting in an unproductive resistance toward modernisation, even as it gains extraordinary pace in 2021. We also delved into the importance of a growth mindset in allowing individuals, and teams, to gain the motivation to thrive in this…

“What if artificial intelligence takes over my job? What if I become redundant?” Every one of us has experienced technology encroaching on our lives, more and more so with each year that passes. It appears that technological innovation is a certainty that is only accelerating in pace. As this innovation intrudes on more aspects of…

Not a lot of people have heard of the term ‘dark data’ before; Gartner defines it as the information assets organisations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetising). Despite its name, it is nothing nefarious. Harnessing this dark…

At MAC we have recently been having discussions about the concept of Data Driven Agility; how can organisations start to leverage data more intelligently in an agile-delivery process, select data which is fit-for-purpose and, importantly, help solve business problems? For anyone who isn’t familiar with agile, here’s a summary: Agile teams are best suited to…

One of the biggest pain points in many organisations – although they might not even be aware of it – is the disconnect that exists between the data analytics department and the other business units. Despite the concept of a data journalist not being well recognised in the industry, the fundamental challenge facing businesses is…

In the preceding articles we have covered topics on building the correct foundations so as to implement data analytics in an organisation with a centralised data function. Using the Sit. Crawl. Walk. Run. Paradigm, we explored how best to embark on a data journey and what steps to take to reach analytical maturity. Finally, we investigated ways…

In the preceding articles we have covered topics on building the correct foundations so as to implement data analytics in an organisation with a centralised data function. Using the Sit. Crawl. Walk. Run. Paradigm, we explored how best to embark on a data journey and what steps to take to reach analytical maturity. Finally, we investigated ways…

In Computer Science, garbage in, garbage out (GIGO), is the concept that flawed inputs will yield flawed outputs, or ‘garbage’. This principle applies to all analysis and logic, in that arguments are unsound if their premises are flawed. In data analytics, it is a mammoth challenge. A famous example of garbage data from history is…

Biological and intellectual advancement in human beings follows a set pattern, as does implementing data analytics into a business. Unfortunately, many organisations want to rapidly ascend from having no analytics to having mature predictive analytics. Often, this revolution-based approach fails to realise the importance of data and analytical maturity. Instead, an evolutionary-based approach following the…