Electronic health record (EHR)–based real-world data (RWD) are integral to oncology research, and understanding fitness for use is critical for data users. Complexity of data sources and curation ...

An article recently published in Nature proposes a new way to evaluate data quality for artificial intelligence used in healthcare. Several documentation efforts and frameworks already exist to ...

To establish a consistent approach to assess, manage and improve data quality across the data lifecycle, covering a wide spectrum of data types, and taking into account the blurred line between data ...

Data quality problems are systemic in agriculture, the researchers note. Historical reliance on local practices, fragmented ...

Data-driven decisions require data that is trustworthy, available, and timely. Upping the dataops game is a worthwhile way to offer business leaders reliable insights. Measuring quality of any kind ...

We’re just starting to tap the potential of what AI can do. But amid all the breakthroughs, one thing is fundamental: AI is only as good as the data it was trained on. Unlike people, who can draw on ...

Observability by definition is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. In other words, a system’s behavior is determined from its ...

The marketing landscape is undergoing nonstop disruption. Rapid innovation and the rise and spread of automation have created an “always-on” culture that’s “connected everywhere” and “streaming ...