Predictive models are a critical component for automated and augmented decision making. As this deployment pattern becomes more widely adopted, two competing priorities emerge. How can we deliver more models faster while being certain of accurate and consistent performance? The key to solving this dilemma is in the automated testing
The infinite game-changer to monetize your analytics opportunities Does your factory still belong to the minor 11 percent saying that 5G is not on your radar? This means your factory is not planning to realize benefits from use cases like remote predictive maintenance, time-critical process optimization, automated visual quality inspection,
The changes we have seen during 2020 have prompted a lot of soul-searching. Around the globe and across industry sectors, companies are looking at ways they can improve how they do business. My conversations with clients suggest manufacturing companies recognize we have reached a tipping point. Adopting analytics and using
Banks don’t like to publicise it, but there’s already a place on most high streets that offers everyday banking services: the Post Office.
Companies have been talking about disruption for years. The word appears in every other top-level business meeting – yet the revolution hasn’t happened. Many businesses have little to show for it. In truth, disruption needs more than enthusiasm. Without a strategy, organisations have simply transformed long, complicated paper processes into
Recent money-laundering scandals have shaken public trust in the banking sector. How can banks rethink their approach to AML? The BBC’s recent Panorama documentary, “Banking Secrets of the Rich and Powerful,” is an uncomfortable watch for anyone working in the banking sector. While all banks have anti-money laundering (AML) teams
I believe the most important part of the analytics lifecycle is defining the business question being asked.
“It doesn’t stop being magic just because you know how it works.” Terry Pratchett, The Discworld Series Welcome to the third, and final, installment of Data Science in the Wild. In Part 1 we were lost in the woods thinking about how to start a data science project. In Part
Machine learning and visualisation help - 250 students enrolled in the program across all years. Now the program started its third year ...
Today’s customer really expects a truly extraordinary customer experience. That means that your company, your brand and the experiences you provide are not just in competition with people in your category. They’re in competition with people like Amazon, Uber and Starbucks, who have managed to make the mobile device a
