This TDWI Best Practices Report explores how organizations are innovating across the data and AI life cycle, spanning modern data architectures, embedded analytics, and generative and agentic AI.

Dhubaib, head of AI and data science at Further, to explore how enterprises are using AI, data, and automation to unify customer experiences and remove friction across the life cycle.

Data storytelling is the practice of building a narrative around a set of data and its accompanying visualizations to help convey the meaning of that data in a powerful and compelling fashion.

Many organizations today are looking to move from traditional BI to AI-powered, talk-to-your-data experiences. Yet most organizations still depend on established BI and dashboarding environments. The ...

Let your résumé show that your in-depth knowledge has been certified by TDWI, the industry’s premier provider of data and analytics education. Recognized by CIO Magazine as the top business ...

I recently spoke in a webinar run by Informatica Corporation, sharing the stage with Informatica’s Scott Hedrick and Ron van Bruchem, a business architect at Rabobank. We three had an interactive ...

Data wrangling and preparation remain some of the most time-consuming steps in enterprise analytics, often slowing down the path from exploration to insight. Emerging AI agents together with ...

TDWI's Best Practices Awards program is designed to identify and honor companies that have demonstrated excellence in developing, deploying, and maintaining BI and DW applications. Winners are chosen ...

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 ...

Meet regularly with each other on a regional basis Share best practices in a small group setting Establish a strong network of peers Gain technical advice and career direction Everyone is welcome. We ...

I was recently on a group call along with several other analysts where IBMers spelled out their definition of big data. They structured the definition by explaining big data’s primary attributes, ...