Data quality issues emerge from multiple failure points from development practices to production life cycle, each compounding others in ways that are detected only at the end: Improper data testing ...

1. The "quarantine" pattern is mandatory: In many modern data organizations, engineers favor the "ELT" approach. They dump raw data into a lake and clean it up later. For AI Agents, this is ...

There are wide discrepancies in data quality for hotel transactions across global regions, with the largest occurring in Asia-Pacific. Because hotels and agencies need to harness data quality to ...

The data purgatory hits major technology initiatives like AI projects when obstacles are created by data accuracy, quality, and accessibility. Fast Company has put a spotlight on the make-or-break ...

Data is critical to every business, but when the volume of information and the complexity of pipelines grow, things are bound to break! According to a new survey of 200 data professionals working in ...

New details from the Bureau of Labor Statistics (BLS) reductions reveal a concerning decline in the quality and integrity of U.S. economic statistics. Cutbacks in Consumer Price Index (CPI) data ...

A global survey by Dun & Bradstreet highlights rising cyber threats and data quality issues in financial services, impacting AI adoption and decision-making. Despite increased risk mitigation spending ...

Marketers suffer from a variety of negative consequences stemming from poor-quality data that collectively drains marketing resources and limits effectiveness. Wasted media spend is the most ...

Anomalo Inc. today launched a new tool that aims to help enterprises keep check on the unstructured information that’s becoming critical to the success of artificial intelligence systems. The ...

Without quality control, even expensive, high-precision radiometers can generate misleading data, according to Solargis' ...