How should a company begin to put in place a data quality management strategy? First, as with all disciplines, IT executives must assess the current state of data in the enterprise. Once they’ve ...

While companies may share common ground when it comes to their data quality problems, data quality tools and strategies are not one-size-fits-all solutions to the problem. Each company should approach ...

It can be tough to manage data manually, and doing so can sometimes lead to errors or inefficiencies. Spreadsheets can get overly complex, and data quality can suffer. This has become a large enough ...

In 2025, enterprises are leveraging AI capabilities to enhance data management. Just like 2023, 2024 was a dynamic year for enterprise data management, and 2025 is shaping up to bring even more change ...

Data quality testing platform Soda Data NV today announced the launch of SodaGPT, a data management platform that uses generative artificial intelligence to help users define data quality expectations ...

The AI revolution shows no signs of slowing down, transforming industries at an unprecedented pace. The fuel powering this change is high-quality, well-managed data. As companies adopt AI, the demand ...

PARK CITY, Utah--(BUSINESS WIRE)--Reltio, the leading cloud-native, SaaS MDM company that accelerates the value of data for businesses, today announced multiple new capabilities within Reltio’s ...

“Data is a precious thing and will last longer than the systems themselves.” So said Tim Berners-Lee, the inventor of the World Wide Web. ‘Precious’ provided the data is indeed trustworthy and of ...

Kore Integrate is the perfect platform to improve Data Quality Management, said Maxwell Dallinga in a recent blog post by Kore Tech. Data quality management is a process to ensure that data is ...

SAN FRANCISCO--(BUSINESS WIRE)--Monte Carlo, the data and AI observability company, today announced a series of product enhancements and new capabilities at its annual IMPACT Data Observability Summit ...

Universities must tighten the quality of the data entered into AI models to improve the output generated by tools such as chatbots. Universities have been cautious adopters of artificial intelligence.

In recent years, there’s been an explosion of tools that allow businesses to connect, transform, analyze and serve data from all kinds of sources. Combined with the increasing pressure on businesses ...