
Self-Service Analytics Is Not Self-Service. But Don’t Tell Anyone - Issue 329
What Anthropic reveals about the data infrastructure, expertise, and human judgment behind successful self-service analytics.
Where product, data science, and analytics intersect.
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What Anthropic reveals about the data infrastructure, expertise, and human judgment behind successful self-service analytics.

How well-designed data models can serve analysts, BI tools, and AI agents without another layer of abstraction

My lessons for testing AI models, tracking execution, and measuring product and business impact.

dbt founder Tristan Handy on how AI changes the work of analytics engineers

How to build a subscription waterfall that gives AI the guardrails to keep churn, revenue, and subscriber metrics accurate

Napkin math for estimating whether to offer a renewal discount - and how low to go.

A new practical framework for deciding when to test, how much data to collect, and when the evidence is worth the cost.

AI adoption does not fail because models are too weak. It fails because companies are too messy for powerful models to understand.

The skills, tools, and responsibilities behind one of the newest analytics roles.

A reading list for analysts and data scientists working at the intersection of data, product, and decision-making.

A deep dive into Omni’s semantic layer, BI-as-code workflow, customer feedback, AI features, and where the tool still falls short.