Updated December 9, 2025
From Governance to Guidance: The Next Phase of AI ReadinessAI Adoption Has Outpaced AI Readiness Every enterprise I talk to right now is chasing the same goal: operationalizing AI agents and agentic analytics. The enthusiasm is there. The budgets are there. The pilots are running. But the confidence? That's…
Updated September 9, 2025
Why 95% of Enterprise Generative AI Pilots Fail & How to Fix the Failure RateThe Harsh Reality: AI Pilots Are Stalling MIT’s NANDA initiative recently published a study showing that “the 95% failure rate for enterprise AI solutions represents the clearest manifestation of the GenAI Divide.” For executives betting big on AI, that number…
Updated August 21, 2025
Retail Analytics Solutions: How to Eliminate Data Silos and Conflicting ReportsA Fortune 50 home improvement retailer with 2,200+ stores was drowning in data chaos. Finance reported one margin number. Store operations had another. Marketing's revenue figures never matched either department. The reconciliation process? A grueling 2-3 weeks of manual Excel…
Updated March 20, 2025
Semantic Layers in Data Strategy: Enabling Governance and DemocratizationRecently, I had the opportunity to join the EDM Council webinar, Semantic Layers in Data Strategy: Enabling Governance and Democratization, alongside industry experts, including Morgan Templar, Chief Executive Officer at First CDO Partners, and Leigh Pence, Data Governance Senior Tech…
Updated November 21, 2024
New Approach to Governance: Reliability, Relevance, and Integrity – How Semantic Layers Ensure Accuracy and Consistency Across UsersIn today's data-driven world, organizations are inundated with vast amounts of data generated from countless sources. The challenge lies in managing this data deluge and ensuring its reliability, relevance, and integrity. A promising solution to this challenge is implementing a…
Updated February 1, 2024
From Data Products to Analytics ProductsThis post was written by Donald Farmer. Donald Farmer is a seasoned data and analytics strategist, with over 30 years of experience designing data and analytics products. He has led teams at Microsoft and Qlik Technologies and is now the…
Updated August 3, 2023
Harnessing the Power of the Semantic Layer for FinOps MasteryIn the world of Finance Operations, or FinOps, the focus is on striking a balance between cost efficiency and fostering speed and innovation. FinOps refers to a financial management practice involving cross-functional teams to manage cloud consumption and costs. This…
Updated June 15, 2023
A Federated Data Model Governance Approach: Insights from Data LeadersI hosted another round of interviews with data leaders about how they deliver AI and BI for their organizations. We discussed the combining of data fabric and data mesh, the hub-and-spoke approach, and the future of a federated model for…
Updated February 7, 2023
Building Guardrails into your Data Mesh with Analytics GovernanceAs we covered in the first three parts of our data mesh series, a successful data mesh approach empowers domain experts to build their own data products with centrally-governed building blocks. And to enable this model, organizations need to facilitate…
Updated January 31, 2023
How to Implement a Composable Analytics Strategy that Supports your Data MeshAs we covered in parts one and two of this blog series, organizations establish data mesh in order to create more widespread, flexible data access across the entire business. And in order to achieve this, a data mesh approach must…
Updated January 17, 2023
Using Self-Service Tools To Speed Up Data Product DevelopmentThis blog is part of a series from Vin Vashishta, Founder and Technical Advisor with V Squared. V Squared advises businesses on AI strategy, data product strategy, transformation, and data organizational build-out services. They have helped clients deliver products with…
Updated January 12, 2023
The Definition of Data Mesh: What Is It and Why Do I Need One?Today’s leading businesses prioritize data mesh. The modern data mesh craze ultimately came about to streamline data democratization – that is, making the right data available to the right people at the right time. Democratization is a huge departure from…
