As artificial intelligence (AI), automation, and more are expected to replace many repetitive tasks, companies around the world are looking to fill skills gaps in IT, data analysis, and even AI itself. . Emerging technology is creating opportunities for the next generation of data professionals who are looking to adapt and leverage their interest in technology into this new era of work. However, the PBT Group says this requires a combination of hard and soft skills that complement training and experience.
“Digital transformation and the evolution to a data-driven business has become a priority for organizations across all industries,” said Andreas Bartsch, Head of Innovation and Services at PBT Group. “And this has created a huge demand for data and digital skills that is proving difficult to meet even internationally.”
According to a 2023 research project by Forbes Advisor, 93% of UK businesses say there is an IT skills gap due to rapid advances in technologies such as AI, data analytics and cloud computing. Additionally, Salesforce’s 2022 Global Digital Skills Index estimates that 14 G20 countries could miss out on $11.5 trillion in cumulative GDP growth if they do not address the digital skills gap.
South African higher education institutions are responding to local demand for digital skills, often in collaboration with industry. Twelve of the country’s leading universities offer graduate qualifications up to bachelor’s and doctoral level to develop specialized data professionals such as data engineers, data architects, and data scientists. These careers are considered “emerging,” so new courses are being added all the time. However, the market entry rate of graduates does not meet demand.
Technical skills remain fundamental
Data-related jobs have expanded exponentially in recent years, with data-based decision-making becoming increasingly critical to nearly every business, from IT infrastructure to finance, marketing, sales, and human resources. We are expanding into this area. Organizations rely on data professionals to manage vast amounts of data and provide the insights needed to meet customer demands while optimizing internal processes.
Given the somewhat technical nature of the data specialist role, exposure to some form of programming (Python, SAS, Java, C++, etc.) is essential when it comes to important ongoing skills. Additionally, Structured Query Language (SQL) is a programming language for storing and processing information in relational databases, and is arguably the “home language” of the data world. Therefore, mastering SQL is most beneficial, regardless of your data specialist role.
Help data professionals adapt more easily by learning how to use more popular data engineering, cloud engineering, and data analytics technologies, such as Microsoft’s Azure and PowerBI, Amazon Web Services (AWS), IBM DataStage or Informatica, and SAS. You will be able to do it. For organizations with a technology stack of choice, most of these technology providers offer accessible training courses and certifications. Some understanding of modern data platform concepts and related best practice principles is also essential.
Bartsch points out, “In addition to this, regardless of the technology, it’s important to remember that great data professionals are technology and cloud agnostic.”
As a complement to hard skills, Nikki Pantland, Data Analyst at PBT Group, emphasizes the importance of soft skills for data professionals to truly succeed and increase their market value in the future. .
The same Forbes Advisor study supports this view, ranking problem-solving, including analytical and critical thinking and troubleshooting abilities, as the most important soft skills for data and technology professionals.
“Soft skills that are equally important include continuous learning, creativity, emotional intelligence, and communication (written, oral, and presentation skills). It’s not just about having technical ability; It’s also important to understand the origins and formation of data, be interested in data, and be able to meaningfully share insights with people outside of the business’ data experts,” says Pantland.
