Organizations addressing data quality issues as a strategic operation are positioned to adapt to latest trends and scale ...

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 the datasets are useful tools for training AI models, they do come with their own risks, from regulatory risks to ...

We collaborate with the world's leading lawyers to deliver news tailored for you. Sign Up for any (or all) of our 25+ Newsletters. Some states have laws and ethical rules regarding solicitation and ...

Unlock AI's true potential with data quality, integrity and governance.

In today's ever-evolving landscape of supply chain management, executives and leaders are facing an intricate web of challenges. To navigate these complexities, advanced analytics and AI have emerged ...

Here are seven simple steps that will help in the extension of data life and will also assist in helping data retain its worth: 1. Data Sources: All data sources must follow stringent protocols of ...

Informatica from Salesforce, a leader in enterprise AI-powered cloud data management, today announced that it has been recognized once again as a Leader in the 2026 Gartner® Magic Quadrant™ for ...

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 ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

Effective quality control (QC) data management is essential for ensuring reliability of reported patient results and regulatory compliance in molecular infectious disease laboratories. This session ...