Hidden Insights
Experience the possibilities with Business Analytics
In my previous blog post, I talked about how both retailers and consumers can benefit from applications of artificial intelligence and discussed some compelling use cases. I would like to take this post a step further and delve into a particular bugbear of mine: the struggle to find the right size. In
Much of the discussion about AI centres on what the algorithms can do, as well as the potential for change and/or disaster. But what about the team behind the algorithms? Few discussions have focused on this most essential group, and not just the modellers, but the data sources, the trainers,
Analytics platforms have a lot to live up to. The scope may be fairly straightforward, but expectations can be high, and there is a wide range of users and customers, all of whom have slightly different needs. This post explores what IT decision makers can expect from an analytics platform.
For part 7 of this series, I had the pleasure of interviewing mathematician, former colleague, and data science “rock star” Longhow Lam. Since there’s no need for an office for his one-person company, we decided to meet for lunch in a very hot (31 degrees) and sunny Amstelveen city
Data governance is not an old concept; at SAS we have been pitching data governance benefits for years. However, it is often seen as something that is nice to have, even though it is a recognized method for mitigating risk, increasing operational efficiency, and enabling innovation. This is the first
Gartner expects artificial intelligence (AI) to create 2 million new jobs by 2025. AI and machine learning are already an important part of business processes and business areas in many companies and organisations, making everyday work easier, optimising interactions with customers, reliably predicting the failure of machines or supporting the