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 ...

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 ...

Arguably, the two biggest challenges in the FAST ecosystem are managing the ad experience and delivering ROI for the brands that support the platform. Evan Shapiro, CEO, ESHAP, Patrick Courtney, SVP, ...

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 ...

When normalizing data structures, attributes congregate around the business keys that identify the grain at which those attributes derive their values. Attributes directly related to a person, ...

This article explains how to programmatically normalize numeric data for use in a machine learning (ML) system such as a deep neural network classifier or clustering algorithm. Suppose you are trying ...