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It’s Essential – Verifying the Results of Data Transformations (Part 2)

Test cases, data, and validation procedures are crucial for data transformations, requiring an understanding of transformation requirements, scenarios, and specific techniques for accuracy and integrity. Data transformations require complex testing due to their sophisticated logic, computations, and dependency on real-time data streams. This necessitates extensive test case design, representative data, automation tools, and robust validation […]

Key Takeaways from the DGIQ East 2024 + AI Governance Conferences

There’s nothing quite like gathering with data professionals – friends old and new – at a DATAVERSITY conference. Last month’s event was particularly special, combining the well-established Data Governance & Information Quality (DGIQ) East Conference with the inaugural AI Governance Conference (AIGov). Adding to the excitement was the expanded Women in Data Management and Governance (WDMG) program. With so much packed […]

How Data Will Reshape Industries in 2025

Data has become a driving force behind change and innovation in 2025, fundamentally altering how businesses operate. Across sectors, organizations are using advancements in artificial intelligence (AI), machine learning (ML), and data-sharing technologies to improve decision-making, foster collaboration, and uncover new opportunities. In the upcoming year, the focus is on making data more accessible, protecting […]

Data Management for Medical Device Clinical Trials: A Guide

Clinical trials for medical devices hold a unique significance due to their direct application in patient care and the rigorous scrutiny they undergo from regulatory bodies. Unlike pharmaceutical trials, medical device trials involve complex interactions between hardware, software, and human factors. This complexity is compounded by the high stakes associated with ensuring patient safety, making […]

Strategies for Managing Data Debt in Growing Organizations

As organizations scale, data debt can accumulate silently, affecting productivity, efficiency, and decision-making quality. Data debt refers to the accrued cost of shortcuts and inefficiencies in data management that may have once seemed expedient but ultimately hamper long-term growth.  Over time, whether it’s due to process changes, platform switching or growth, organizations find themselves boggled down […]