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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…
Navigating AI and Data Science with Data Vault
Navigating Your AI and Data Science Initiatives to Success with Data Vault Artificial Intelligence can be complex and difficult for businesses to adopt and implement successfully. Business leaders can be nervous about going into the breach with AI. Business executives may even float plans to implement AI while privately leaving it to the next CTO…
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…
From Data Platforms to Information Systems: The Shift Analytics Has Yet to Make
This article examines the systemic authority fracture hindering the evolution from data platforms to integrated information systems in enterprise analytics. It highlights how misaligned decision rights and accountability create persistent fragmentation, deferred decisions, and operational friction. The analysis includes observable patterns that reveal this failure mode and a realistic scenario illustrating its impact on funding and governance. The article concludes by reframing analytics decisions to focus on governance alignment rather than technology upgrades, exposing the hidden costs of inaction.
Zero Trust for Data: When Sensitive Is a Label, Not a Control
Zero Trust for data reframes “sensitive” from a label into an executive expectation that access is bounded, continuously verified, and provable. The core liability emerges when permissions, copies, and usage pathways expand faster than the enterprise can constrain or evidence them. Access sprawl becomes a rational outcome of delivery pressure, reuse incentives, and reluctance to remove entitlements once granted. Analytics and AI intensify the problem by multiplying derivatives and consumption paths that outlive their original justification. The article contrasts a technology upgrade posture with a system redesign posture and explains where incentives and authority collide. It closes with executive questions that surface whether governance can be enforced and demonstrated, not merely documented.
What Is a System of Information Management and Why Governance Alone Cannot Provide Defensibility at Scale
A System of Information Management (SIM) is an enterprise capability that integrates people, processes, and technology to preserve data meaning, lineage, and accountability over time. Governance frameworks alone express intent but lack the operational mechanisms to provide auditable evidence and sustain defensibility at scale. As organizations grow and adopt AI-driven analytics, risks of definition drift and fragmented accountability increase without a systemic approach. SIM distributes accountability across roles embedded in workflows, contrasting with traditional governance models. This explainer clarifies why SIM is essential for long-term trust and compliance beyond governance policies.
