The dramatic surge of artificial intelligence (AI) across industries has spurred numerous perspectives about its potential impact on the job market.

Picture this: Your smart refrigerator would soon be able to sense your groceries and milk supplies that need replenishment. This list will be automatically sent to your Smart Digital Assistant (Alexa, Google Home, etc.), which in turn will send it to an automated chatbot within the premise of your local departmental store.  

Result: Fresh supplies delivered, as required, without your intervention.  

With the cloud transformation wave taking businesses by storm, it is essential to have special infrastructure tools and architecture to leverage automation and built-in security for superior migration and economics. However, for many businesses, the foundations of their on-premises IT systems were built years ago, and people who set up these systems might have already left the organization.

There is a lot of hype around data. It is billed as a route to better citizen service, faster business decisions and overcoming enterprise silos. But it’s not that easy; every data decision is dependent on resolving the lack of trust, misalignment and data silos.

As outlined in our previous blog, Data virtualisation and efficiently exploiting the power of the information contained in an organisation comes with its own challenges. In this blog, I’ll outline some of the challenges I have experienced and give some tips on how to navigate your way through if you have similar issues.