Learn the definition of data quality and discover best practices for maintaining accurate and reliable data. Data quality refers to the reliability, accuracy, consistency, and validity of your data.

When generative artificial intelligence (genAI) burst into prominence with the release of ChatGPT in 2022, technically savvy business users quickly began experimenting. At that time, existing tools ...

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 ...

Unlock the power of your data with an effective data governance framework for security, compliance, and decision-making. Data governance frameworks are structured approaches to managing and utilizing ...

A company’s content lies largely in “unstructured data”—those emails, contracts, forms, Sharepoint files, recordings of meetings and so forth created via work processes. That proprietary content makes ...

In this podcast, we talk with Cody David, solutions architect with Syniti, which is part of Capgemini, about the importance of ensuring data quality for artificial intelligence (AI) workloads. Being ...

New research from the Data Provenance Initiative has found a dramatic drop in content made available to the collections used to build artificial intelligence. By Kevin Roose Reporting from San ...

The Asian American health narrative is situated within the complex interplay of racialized history, immigration patterns, and policies regarding Asians in the United States—a dynamic that has ...

Opinions expressed by Entrepreneur contributors are their own. Over the past year, we’ve realized the world is not as it used to be anymore. We’ve learned that it is nearly impossible to prepare a ...