Lost in translation: Why semantic chaos is the real AI risk
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.
Data product reusability: Cut costs & scale AI with 3 key changes
Learn how to increase data product reusability to drive faster decisions, stronger AI outcomes, and measurable business growth.
How Anetac expands the Quest Security Management Platform for full-lifecycle identity security
Quest Software offers a unified approach to identity security across all six pillars of NIST CSF 2.0, now with live access-chain intelligence from...
The cost of standing still: what data inaction really risks in an AI-driven market
Data inaction compounds competitive risk. Learn what delaying governed data products costs your organization and how reusable data assets close the...
Identity-first security: The future of resilience
With identity-first security, Quest helps protect and recover Active Directory against ransomware, insider threats, and quantum-era risks.
Reuse over rebuild: How trust can unlock the real value in your existing data
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...
Three reasons organizations use SharePlex for Oracle-to-Databricks data movement
Learn how Quest SharePlex uses log-based CDC to move Oracle data into Databricks as Parquet files, with less latency and no impact on production...
erwin Data Intelligence 15.1
AI doesn’t have a data problem. It has a navigation problem.
AI data governance is the missing navigation layer for enterprise AI, providing the context, meaning, and direction required to drive AI success.