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

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 ...

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, ...

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 ...

A wide variety of methods can be used by organizations to collect data, including websites, social media, POS systems, surveys, petitions, apps, and financial records. With data management, businesses ...

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 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 ...