This research initiative highlights practical AI and business analytics for decision support across infrastructure, ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

Buy-side firms are consistently faced with burgeoning volumes of data, necessitating adept management of expansive data extractions, a task fraught with intricacies and considerable costs. Arthur Orts ...

As artificial intelligence technology continues to improve, more companies have become interested in machine learning—technology that is able to “learn” and adapt to become increasingly adept at ...

No matter the size or scope of an organization, there is little question that everyone wants to find ways to improve their performance. Baseball teams use sabermetrics; companies often use the stock ...

Real estate is a massive (and complicated) part of agency operations. Leading-edge analytics help make the most of existing footprints. Rana Lahiri, left, and Mark DeRosa say improved analytics can ...

However, knowing what specific data is valued is fundamental in effectively scaling up an analytics model, as the goal is to produce more of what you value. Let’s consider class attendance as a ...

Data analytics can be a tough topic to teach. There’s no real road map for instructors to follow, and the technology that underlies it can change at a rapid clip. What’s more, students often have ...

Data modeling tools play an important role in business, representing how data flows through an organization. It’s important for businesses to understand what the best data modeling tools are across ...