TDWI instructor Chris Adamson defines dimensional data modeling as “the nexus of a holistic approach to managing business intelligence, analytics, and governance programs. Used at a program level to ...

Data visualization and visual data discovery can enable diverse types of users—from data scientists working with big data to nontechnical business managers and frontline users—to see significant ...

Nothing can ruin analytics faster than bad data. If users lose trust in the data, they will lose confidence in analytics and be unable to put insights into action. Organizations are facing new ...

TDWI research shows that while organizations cite generative AI as a top priority, most are struggling with implementation and lagging in maturity. Join us for an insightful TDWI Summit event where ...

Enterprise data quality management can only become a universal practice if it is transformed from the specialized practice of a core group of data stewards into something that all knowledge workers ...

Technologies are evolving at a breakneck pace, and business demand for data and analytics is expanding. Learn how to modernize your platforms and architecture to meet the challenge of delivering data, ...

Advances in machine learning, advanced AI, and deep learning are opening new frontiers in the search for data-driven competitive advantage. As new and evolving technologies become accessible for ...

Learn to bring business intelligence and analytics capabilities to growing audiences, foster data literacy, and develop a data-centric culture for competitive advantage. From the delivery of modern ...

Successful modern data infrastructure encompasses more than just storage and staging options. Organizations must take a holistic approach with key data management practices including data quality, ...

Why Google is a Leader and positioned furthest in vision among all vendors evaluated in the 2024 Gartner Magic Quadrant for Cloud Database Management Systems Google’s strengths and challenges among ...

Your enterprise already uses operational data—such as customer information, financial transactions, and inventory levels—to improve processes and customer experience. But if this information isn’t ...