Marketing teams have been struggling for years to adjust to their changing roles amid digital …
As we start a new decade, the top trends for business analytics platforms are cloud, artificial intelligence, automation, on-device (edge) analytics, and augmentation. Cloud ecosystems empowered with AI have matured greatly in recent years. Smart, augmented prediction and decision-making tools are at a stage where they are ready to be deployed across organizations, from the boardroom to the shop floor. The challenge is making sure your business is ready to use them.
Today’s HR teams potentially have access to huge amounts of data, and this can bring great rewards for those who use that data intelligently. But, data also brings its own unique challenges. Therefore, before implementing any data-driven HR approach, it’s important to consider the potential pitfalls that surround employee-related data, particularly when it comes to their personal data.
In the last few years, we’ve seen incredible advances in data, analytics, and artificial intelligence (AI). While there is understandable concern about what this means for human jobs, I still believe this is an exciting time for businesses – and the people who work in them.
As AI and machine learning continue to develop, the way we use analytics also continues to grow and change. While in the past, businesses focused on harvesting descriptive data about their customers and products, more and more, they’re about pulling both predictive and prescriptive learnings from the information they gather. So – what is the difference between descriptive, predictive analytics and prescriptive analytics? And do you need the latter in your company?