Machine learning models can’t always handle reality (but most humans can)


A growing number of enterprise leaders view artificial intelligence (AI) and machine learning (ML) as transformational technologies that can enable better decision-making, increase efficiency, eliminate human error, and lower costs. For many enterprise workers, however, the relentlessly consistent performance promised by intelligent machines looms as a threat to their jobs. After all, what human can […]

Context turns big data into knowledge

It’s really hard to understate the importance of context— especially when it comes to data. Data is great, but it’s meaningless and even cumbersome without context. Put a sign up saying “Keep Out,” and most will ignore it. Put one up saying “Keep Out, Unexploded Bomb” and all but a foolish few will stay away. Data in […]

Keeping it real: Why your data program needs a data steward

Big data analytics offers enterprises the opportunity to uncover hidden value in their data assets. But as discussed in a recent post, data can’t analyze itself. Data scientists and other enterprise employees dependent on data analysis to do their jobs must ask the right questions and draw the correct conclusions from the data. Both bad […]

What do data analytics pros need from IT? Plenty!

Enterprises want and expect a lot from their data analytics initiatives and their data science professionals, including greater insights into customers, markets, business processes, logistics, employee performance, and much more. If that seems like a lot to ask for, well, it is. But something that gets overlooked in the conversation regarding what data analytics can do […]