[Column] Adebayo Sanni: Managing the autonomous evolution
Humans are 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.
Managing this growing flood is complex and the task comes with a high level of responsibility. But throwing more bodies at the problem isn’t efficient or even a guarantee of success. The 24/7 requirements on business and huge security challenges mean that ‘manual” management is no longer an option.
The key lies in the use of Artificial Intelligence (AI), Machine Learning (ML) and automation. Particularly when combined together they will let businesses manage and get value from their information more easily, effectively, and with less effort. One technology in particular that is unlocking new levels of value is the autonomous database.
Nigeria accounts for nearly 50% of West Africa’s population and the country has one of the largest populations of youth in the world. 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.
Managing the data challenge
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.
The autonomous database is 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.
According to a recent Harvard Business Review Analytic Services survey, so far few organisations have 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.
While this change certainly won’t happen overnight, respondents are expecting to significantly increase their use of intelligent automation over the next three years. With that the case, business and IT leaders need to start considering how to move along their automation journey from basic adoption to full intelligent automation.
To get there, a substantial amount of change will need to happen, not least in the digital transformation of data, skills, processes, and culture. Intelligent automation requires a corresponding upgrade in skillset. Database administrators must be encouraged to seek new certifications and experience, building on their existing core skill set.
Just imagine, all those incredible minds, currently dedicated to tuning, patching, securing and managing databases, applied to more valuable activities, such as improving data architecture, securing external data sources, and otherwise ensuring the business is making the best possible use of data.
As more data continues to be generated each day, there will be even more pressure on businesses to make the most of the data available. Database management will be more crucial than ever before, and emerging technologies like autonomous will soon become the norm as they help businesses boost innovation and financial gains.
Last year, Oracle Academy announced a collaboration with the Federal Ministry of Education of Nigeria (FMoE) to create new computing education pathways for local students. Through the agreement, FMoE plans to integrate Oracle Academy computer science curriculum and resources across 10,000 academic institutions across the country, reaching over 1.5 million students within the region. Over the next three years, Oracle Academy will also facilitate the training of 4,000 educators at the secondary and higher education levels to teach computer science.
Earlier this year, Oracle Academy hosted Knowledge Builder sessions with STEM university students. They were provided with guidance on technology career paths and industry relevant skills as well as practical sessions on artificial intelligence, data analytics, machine learning and data visualisation cloud services.
From a country standpoint, Nigeria is ready to start the drive towards autonomous technology. Now the focus is on getting the skills in place to capitalise on the willingness to change.