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

Generic industry data models do have a place, but they serve as a kick-start to the modeling process, not the destination. Consider an address; organizations may break address components apart in ...

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 ...

Why normalizing your clinical and claims data into standard terminologies is critical to supporting forward-thinking initiatives such as big data analytics, population health management and semantic ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. AI‑generated code creates implicit ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

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 ...