A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource efficiency and cost improvement.

Over the years, we've seen a couple of different organizational models for delivering analytics to the business. While both models have their advantages, each model has some severe drawbacks that make ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

Big data is less predictable than traditional data, and therefore requires special consideration when building models. Here are some things to keep in mind. Image: iStock/z_wei Data modeling is a ...

Google's open-source Meridian helps marketers build better models, understand lift by channel and finally bring sanity to their measurement strategies. Necessity is often called the mother of ...

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 ...

This article is part of a VB special issue. Read the full series here: The quest for Nirvana: Applying AI at scale. Artificial intelligence (AI) relies heavily on large, diverse and ...

Large language models already read, write, and answer questions with striking skill. They do this by training on vast libraries of text. Once that training ends, though, the model’s knowledge largely ...

In today’s data-driven world, the demand for skilled data analysts is growing rapidly. Businesses rely on data to make informed decisions, and Excel remains a core tool for data gathering, cleaning, ...