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Episode 2: Defining and Solving Business Risks
Join Us for Unlocking the Vault with Dan Linstedt Audit compliance, global security, distributed privacy policy, and insuring raw data is available for data scientists are just a few of the business risks we face…but are all tackled with the DV2.0 methodology. In this episode, Dan outlines some of the most vexing problems encountered by business…
Why Modern Analytics Fails to Scale Sustainably
Modern analytics initiatives often fail to scale due to a systemic fracture between decision rights and accountability. This misalignment leads to fragmented ownership, repeated rework, and deferred decisions that undermine sustainable growth. The core issue lies in governance and operating model design rather than technology alone. Understanding this fracture clarifies why technology upgrades alone cannot resolve scaling challenges and highlights the political trade-offs involved in realigning authority and incentives.
The Analytics Confidence Gap: Why Trust Fails Before Accuracy
The analytics confidence gap reflects persistent trust issues despite accurate data processes. This gap arises from a structural split between decision rights and accountability for analytic meaning. Accuracy alone does not resolve this fracture because it is embedded in organizational authority, not data quality. Inspecting version control artifacts reveals where semantic authority resides and whether trust can be anchored. Understanding this boundary clarifies why trust often fails before accuracy in enterprise analytics.
FAQ About Data Vault 2.0
This post is a short Q&A of frequently asked questions that I get all the time. Whether you’re just getting started with Data Vault, or are fully certified, there is something here for everyone. If you find that you have additional questions for me, feel free to use the contact-us form on our site to…
AI in Analytics – Reshaping Insight
AI in Analytics: How Intelligence Is Reshaping Architecture, Data Flow, and the Future of Insight There’s a quiet shift happening in enterprises everywhere—a shift that feels less like a trend and more like a turning point. At first glance, it looks like “AI for analytics,” but once you look beneath the surface, you see something…
Relational Thinking Beyond SQL Assumptions
This article examines a workshop at the Worldwide Data Vault Consortium 2026 that addresses gaps between SQL usage and relational theory. It highlights why relational rigor is essential for maintaining semantic clarity and trust in data systems. Key topics include nullology, view updating, and the Closed World Assumption. The discussion exposes how common SQL practices can undermine auditability and correctness in enterprise analytics.
