When it comes to implementing AI, underestimating the importance of data management and governance can lead to both low adoption and slow implementation.
With this in mind, an organisation's data management strategy needs to enable both machine and people to access data securely, easily and as fast as possible. It's also important to establish privacy and security controls.
So says Tinus Visagie, head of Data Integration: Regional Operations at Absa Group,
who will be presenting a case study on ‘Knowing your infrastructure requirements for AI’, at ITWeb Artificial Intelligence 2019, to be held on 20 August at The Forum in Bryanston.
“Infrastructure for AI should be considered a three-legged stool, where the legs are the network, servers, and storage. If any of the legs are not performing, it will affect the overall performance,” says Visagie.
One of the major building blocks for a successful AI strategy is a modern data platform, such as Hadoop, to help the business organise unstructured data. “This data platform will also require a stable infrastructure,” he adds.
During his session, Visagie will share advice for building an infrastructure that enables AI. He will also provide delegates with some key questions to help determine their AI readiness, as well as identify focus areas before embarking on an AI project.
Share