Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with ...

This is the second in a series on what’s still broken in the analytics space. Part one dealt with data ownership, part two will address technology and part three will focus on people and processes.

It’s tempting just to replicate all databases in the cloud, but it’s a much better approach to get your data house in order as part of the move. Last week I discussed database normalization as a best ...

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

It’s time for traders to start paying attention to a data revolution underway that is increasingly impacting their ability to both scale their business and provide value to their clients. Capital ...

Whenever you deal with mathematics or normalization statistics, you will often need to take a large set of numbers and reduce it to a smaller scale. This is usually done with a normalization equation ...

Many people seem to become filled with anxiety over the word “normalization.” Mentioning the word causes folks to slowly back away toward the exits. Why? What might have caused this data modeling ...

Comparison of expression data requires normalization. The optimum normalization method depends on sample type, with the most common being to normalize to reference genes. It is critical to select ...