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Build vs buy is back for data leaders. Buy catalogs, lineage and quality by default. Build only what sets you apart. Here’s how to decide and blend both.

AI initiatives fail when data foundations aren’t ready. Learn how an automated data product factory closes the trust gap, delivering trusted data in days.

Agentic AI increases the risk of cascading failure across data systems. Learn why you need data infrastructure built for autonomous AI.

Learn how a semantic layer can reduce AI costs by providing the context, reusable business knowledge, and trusted data foundation enterprise AI requires.

AI can generate a data model in seconds, but speed isn't governance. See what separates governed AI data modeling from a one-off chatbot output.

See how organizations across industries replaced SAP PowerDesigner with erwin Data Modeler, gaining stronger governance without downtime or lost data.

Five patterns from 25 customer meetings show why AI-ready data products stall on delivery, governance, and readiness. See what leaders shared.

Data modeling for AI requires consistent semantic definitions. Learn why ungoverned data foundations are the root cause of unreliable AI outputs.

AI scales fast on whatever meaning you give it. A semantic layer for AI ensures it works from one trusted definition to dramatically reduce risk.

Learn how to increase data product reusability to drive faster decisions, stronger AI outcomes, and measurable business growth.

Data inaction compounds competitive risk. Learn what delaying governed data products costs your organization and how reusable data assets close the gap.

New APAC research reveals that even mature data programs struggle with reuse. Learn why visible trust signals are the key to closing the data trust gap.