AI success requires more than experimentation—it demands clear strategy, strong governance, repeatable processes, and the ability to deliver measurable business value. This seminar brings together ...

Context, Control, and Enterprise Scale March 31, 2026. Artificial intelligence has entered a new phase of enterprise adoption. Generative ...

Weakness at quantitative reasoning: LLMs struggle with rigorous numeric analysis compared to traditional BI tools. They often commit arithmetic errors in multi-step calculations. They may misinterpret ...

The AI Impact Awards don’t celebrate what AI could do — they honor what AI is doing right now, in real organizations, with real results. The TDWI AI Impact Showcase & Awards is a regional event series ...

AI systems consume data, and their outputs depend on the quality, context, and governance of their inputs. Organizations that treat data as managed products, with clear ownership, documented semantics ...

Master data management expert David Loshin explains common MDM misconceptions, why MDM can be such a struggle, and the keys to having a successful MDM project. David Loshin is an expert in master data ...

Artificial intelligence (AI) provides the opportunity to transform organizations, but there are also downsides and risks to using AI. It’s important for businesses to separate the hype from reality ...

TDWI research shows that data governance remains a top data management priority for 2026, yet most organizations are still stuck in the middle stages of maturity. The rapid growth of AI, new data ...

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 ...

Most organizations have run AI pilots. Far fewer have moved them into production. The gap is rarely about the models themselves; it sits in the data underneath. AI systems working from fragmented, ...