ITWeb: What are the top three opportunities network-enabled computing devices and machine learning technology present to organisations in South Africa?
Mckenzie: Traditionally, the choice has been between embedded solutions that were either difficult to customise or not customisable at all and a small-footprint computing platform that, whilst customable, tended to be expensive.
IOT allows the possibility to add intelligence at a much lower cost. These devices now communicate using standard network protocols which allow for the real-time collection of data on an unprecedented scale. The combination of smart, networked devices and machine learning allows you to build real-time predictive models that can be used to drive decision-making at a pace that was previously difficult to achieve.
ITWeb: Can you highlight three challenges specific to these technologies?
Mckenzie: Challenges that arise from these technologies include security and privacy concerns, maintenance of the distributed software platform and dealing with the huge volumes of data that are generated.
ITWeb: What important points would you like organisations to consider in terms of managing the risks when it comes to IOT and machine learning?
ITWEB: What key points would you like the delegates attending the Enterprise Mobility event to take away with them?
Mckenzie: Firstly; that IOT and ML solutions can unlock new business models and opportunities; secondly solutions can be built using IOT and ML technologies today and lastly that in many cases using skills that you already have access to. The risks associated with these projects are manageable if you consider them up front.