Cloud, AI, data governance and DataOps remain top Big Data trends in South Africa

28th January 2022 By: Schalk Burger - Creamer Media Senior Deputy Editor

The most relevant Big Data trends for South Africa will centre on the familiar themes of cloud adoption and data platform readiness, the maturation of artificial intelligence (AI) models into operational uses, while data operations (DataOps) formations in organisations are expected to mature and data governance and cybersecurity remain vital, says data analytics services company PBT Group head of innovation and services Andreas Bartsch.

The global Big Data market is forecast to top $70-billion by the end of this year and to expand to more than $103-billion by 2027. Making sense of this data will be a key differentiator for any organisation in the connected world, he says.

Organisations have seen how effective cloud systems can be to manage a hybrid workforce. However, more than a singular approach, it is the hybrid and multi-cloud that will gain increasing traction in South Africa, he adds.

Further, business and technology leaders have significant cost implications to consider with cloud adoption, which will see data platform readiness continue to increase in importance.

“Things like data architecture, data modelling, data engineering and data governance remain key ingredients to a successful data and analytics strategy, and even more so in preparing for the rocky path to the cloud,” Bartsch highlights.

Meanwhile, the push to reduce time to market on data products driven by the increasing automation resulting from AI, will see DataOps mature inside the organisation.

“The merging of data pipeline processes and information technology operations will help to improve the velocity, quality and predictability of these data and analytics environments. DataOps will strengthen collaboration, orchestration, monitoring and ease of use, along with much-improved maintainability when it comes to data and analytics,” says Bartsch.

Additionally, a well-designed data architecture will be essential to analytics and AI projects. Having this in place will make the integration process with AI and machine learning (ML) not only faster to do, but also more robust when navigating the complexities of legacy systems.

“AI will become smarter at an accelerated pace. Companies will more easily migrate from pilot projects into more practical ones as they start operationalising the AI models they have running. It is now about creating an internal product from AI that focuses on automation and managing the repetitiveness of tasks,” he says.

“AI and ML technologies are expected to become indispensable as more businesses become data-driven and garner the insights necessary to differentiate themselves on the global stage,” notes PBT Group data analyst Chad Gouws.

Further, from a governance perspective, machine-driven models to automatically monitor for breaches and identify potential vulnerabilities in data systems will be a significant area for growth. Cybersecurity providers will leverage this to monitor customer networks in real-time and proactively identify weak points to mitigate against the risk of them being exploited.

“At a fundamental level, data will remain a key ingredient to any digital transformation strategy. With the ongoing regulatory and compliance pressure on organisations, this component of a digital transformation could very well assist in enforcing the focus on all aspects of data governance, namely people, processes and technology,” says Gouws.

“[Data governance] provides an opportunity for the business to use data governance to necessitate ownership and replace certain structures and put in place the means of establishing a data-driven culture. Getting the basics right will be critical to success when it comes to data and analytics,” concludes Bartsch.