‘How AI, ML Skills Will Address Autonomous Evolution of Data’

Adebayo Sanni

By Emma Okonji

The Managing Director Oracle Nigeria, Mr. Adebayo Sanni, has come up with solutions on how best to tackle autonomous evolution of data generation that has since doubled in the last two years.

Sanni, in a statement, said humans were now generating an estimated 2.5 quintillion bytes of data every single day with more data being created in the past two years than in all of human history.

He, however, explained that managing the growing flood of data is becoming complex and the task comes with a high level of responsibility.

According to him, the key lies in the use of Artificial Intelligence (AI), Machine Learning (ML) and automation, adding that when combined together, they will let businesses manage and get value from their information more easily, effectively, and with less effort.

Recent statistics show that Nigeria accounts for nearly 50 per cent of West Africa’s population and the country has one of the largest populations of youth in the world.

Citing the population size, Sanni said: “This sees Nigeria in the enviable position where it can start building skills for the data-driven environment. With data becoming the currency of business today, establishing skills must be a priority. This leads to an understanding of how data can deliver on what is required and help guide autonomous technology to extract the best value out of it.”

Addressing the challenges in managing data, Sanni said: “The value of data is not in its abundance, but comes from analysing and understanding data and using it to make better decisions. So just as mechanical automation helped traditional manufacturing industries to benefit from economies of scale, software automation can free up valuable human resources from mundane administrative tasks.”

“Forward-looking organisations are already embedding AI and ML technologies into their critical business systems and processes, with key areas of the business predicted to benefit the most from this type of automation being operations, customer service, decision support, IT and finance. With AI and next generation cloud services becoming established, the autonomous database has arrived. Embracing core traits of being self-driving, self-securing and self-repairing, it offers unprecedented availability, performance, and security – helping eliminate human error,” Sanni said.

He explained that autonomous database was set to revolutionise data management, helping boost the speed of insight and driving significant increases in productivity.

“With a self-driving system that uses built-in machine learning algorithms to manage itself, businesses can lower costs and increase productivity whereby manpower can be optimised and resources can be deployed to higher value tasks. This can be through tasks such as redefining data strategy, deriving actionable insights from data, and designing robust systems with business impact,” he said.

Citing a recent Harvard Business Review Analytic Services survey on data, Sanni said so far few organisations had made the move to intelligent automation to any significant extent – for a number of reasons.

“As with anything new, it takes time for adoption – companies need time to get their heads around how these emerging technologies can fit into their current enterprise systems and just how to do that within their existing budgets, skills and culture,” he said.

He advised that a substantial amount of change would be needed to address technology skills gap, adding that intelligent automation requires a corresponding upgrade in skill set.

“Database administrators must therefore be encouraged to seek new certifications and experience, building on their existing core skill set,” Sanni said.