Data is essential for the success of any artificial intelligence (AI) project, but understanding what makes data beneficial—or harmful—for AI is crucial. At a high level, machine learning (ML) and AI ...

Artificial intelligence has moved well beyond experimentation. In my work with organizations that rely on recorded conversations and documented dialogue, I’ve seen how AI now summarizes meetings, ...

By Dr. Kofi Anokye OWUSU-DARKOGhana’s National Artificial Intelligence Strategy (2025–2035) reflects an ambitious vision for the country’s digital future. It seeks to harness artificial intelligence ...

Introduction Data quality in electronic health records (EHRs) is central to data-informed healthcare. Health professionals play a key role in ensuring data quality yet the complexities of clinical ...

Larry English will call for a new set of rules and regulations to make companies and other organisations improve their information quality and reinstate the customer as king at a forthcoming data ...

We cover the seven leading data quality solutions that simplify the work of data management and help turn all those cell values into something that can be used for business decisions. It can be tough ...

Data quality is paramount in data warehouses, but data quality practices are often overlooked during the development process. The true measure of an effective data warehouse is how much key business ...

In this episode of Need to Know, our series covering the topics and issues influencing markets and the global conversation, Michael Beal, Co-Head of Enterprise Data Science at Bloomberg, discusses the ...

Nomenclature is important. Data governance, data integrity, and data quality are all widely used terms, but what do they actually mean and how are they connected? The purpose of this article is to ...