Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

The benefits of data standardization within the social sector—and indeed just about any industry—are multiple, important, and undeniable. Access to the same type of data over time lends the ability to ...

Major data standards frameworks aim at collaboration WASHINGTON, DC, UNITED STATES, January 26, 2026 /EINPresswire.com/ ...

Data is the lifeblood of the modern economy. Thousands of data points generated by each person are helping many industries deliver better products and services—online retailers suggesting and shipping ...

Food companies and consumer groups say the need for uniform data across different input systems is among several challenges to compliance with a looming FDA food traceability rule. During a public ...

As private markets continue to grow, fund managers are increasingly turning to AI to improve efficiency and free up time for ...

As insurance and retirement service providers navigate today’s complex landscape, data standardization and centralization have become critical as firms implement new technologies and leverage data in ...

Data standardization across the municipal market will likely take years and much discussion to pinpoint the issues and how the market can solve them. Processing Content Some of the apparent problems ...

“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Carolina Abenante, co-founder of NYIAX.