By Pete Stiglich
Identifies core data management practices that enable real trust in data: strong data governance with meaningful business participation, robust data architecture and modeling, disciplined data profiling and quality checks, and effective metadata management. The article argues that trust fails when initiatives are IT-driven without stewardship, when quality is neglected, or when business meaning is poorly understood. It emphasizes that governance is the bridge between IT and business, and that profiling plus metadata provide the evidence needed to verify data against defined rules—so trust is earned through controls and measurement.
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Pete Stiglich: Trusted Expert in Data Architecture & Modeling
Pete has over 30 years of data architecture, data management, and analytics experience, most of that time as a consultant in industries such as government, finance, healthcare, insurance, and more. He is an industry thought leader in data architecture and data modeling and has developed and taught many courses on these topics. Pete enjoys helping clients solve complex data problems, leveraging proven approaches such as “Modeling the business before modeling the solution” which provides a benefit to clients that many IT professionals miss.
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