Data, AI, & Machine Learning

What do you do when you’ve got an unending stream of quality data, and processes in place for analytics… but you’re not sure what to do with it all?

Increased access to data can be turned into better decision making by focusing on both the production and consumption of analytics.

Advanced digital technologies are swiftly changing the kinds of skills that jobs require.

Companies that are experienced in using analytics successfully offer five lessons for corporate leaders.

Analytics acts as an amplifier for business processes — but companies should keep four principles in mind to avoid increasing “noise.”

The Echo Nest, a “music intelligence” company, uses machine-learning technology to connect people with new music.

What differentiates data scientists from other quantitative analysts? It’s partly their skill set and partly their mind set.

By 2020, most new data will be generated not by people but by sensors and embedded, intelligent devices.

Data analysts may have external agendas that shape how they address a data set — but a savvy manager can identify biases.

When it comes to big data, GE avoids warehousing and instead turns to the data lake approach.

As business moves to a real-time, data-driven focus, the search for talent has undergone a quantum shift.

Can we automate enough of what data scientists do to ease the skills gap?

Simulations can help shrink the gap between what analysts try to explain and what decision makers understand.

The NFL’s CIO discusses the organization’s customer-focused approach to big data and analytics.

As sensors and computer-mediated transactions become universal, Google’s Hal Varian warns that organizations need to prepare for a flood of data.

If you think analytics is just about the math, you’re telling yourself the wrong story.

Stories of your competitors’ analytics prowess are probably overblown — so take steps to move forward now.

Companies are having a tough time finding the data scientists they need — but that doesn’t mean those projects need to halt altogether.

A company that wants to successfully use analytics needs to make sure its data scientists are fully integrated into business units.

Kaiser’s John Mattison describes the data-driven healthcare system of the future — and says companies need to get in gear to meet its challenges now.