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 ...

In healthcare, the costs are not merely financial. Incomplete, inconsistent or delayed electronic health records can lead to ...

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 ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We’re just starting to tap the potential of what AI can do. But amid all the breakthroughs, ...

Data quality in the modern economy, where data-driving action is critical to business success, can no longer be perceived as mere tech detail. Business leaders increasingly use data to make strategic ...

Many organizations nowadays are struggling with the quality of their data. Data quality (DQ) problems can arise in various ways. Here are common causes of bad data quality: Multiple data sources: ...

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 ...

Utilities are becoming increasingly skilled at adapting to changes brought on by the digital age: pressure from automation, disruption from new technology, and challenges with how to ingest, manage, ...

The true measure of an effective data warehouse is how much key business stakeholders trust the data that is stored within. To achieve certain levels of data trustworthiness, data quality strategies ...