What Most AI Readiness Assessments Get Wrong
Most AI readiness assessments focus on data quality and infrastructure. These matter, but organizations that score well on both still fail to ship AI. Here is what a useful assessment actually measures.
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Notes from the Nextekk team.
Azure, AI, data analytics, and what we have learned shipping them, written for the people who actually build and run the systems.
Showing 1–7 of 7 posts.
What the Azure OpenAI Demo Doesn't Show You
The demo works. Three months into production, the same system is producing wrong answers on a predictable subset of inputs, costs three times what was projected, and has no mechanism to detect when it is failing. Here is what the demo leaves out.
Why Your Power BI Deployment Isn't Getting Used
The most common Power BI failure is not a technology failure. The reports work, the data refreshes, the dashboards load. Nobody opens them. Here is why, and what to do about it.
Digital Transformation Programs That Actually Finish
Most digital transformation programs do not fail because of technology. They fail because of how they are sequenced, governed, and connected to business outcomes. Here is what separates the ones that ship from the ones that stall.
The Real Cost of Putting Data Governance Off
Data governance has a reputation as overhead — something you do because the auditor asked, not because it changes how the business operates. That framing is wrong, and it gets more expensive the longer it persists.
Five Signs Your Cloud Migration Is Going Sideways
Cloud migrations fail in recognizable ways. The technical work is usually not where the failure happens. Here are five warning signs and what to do about each one.
Microsoft Fabric vs. Synapse: How to Actually Choose
Microsoft has two major data platform offerings that overlap in ways the documentation does not fully explain. Here is a practical decision framework — without the marketing language.