Executive Dashboard Consulting: Deliverables That Work
A practitioner’s guide to scoping, building, and rolling out an executive dashboard that leadership trusts—definitions first, charts second.
9 min read
Analytics engineering
Analytics engineering practice
How modern data teams are structured, staffed, and run — and the habits that separate the fast ones.
Data Warehouse Cost Allocation by Team, Product, Workload
A practical path from an opaque warehouse bill to a defensible cost ledger. Concrete Snowflake and BigQuery patterns, tags, roles, reservations, and showback/chargeback.
6 min read
Analytics Engineering Audit: Architecture, Process, and Team
A practitioner’s analytics engineering audit: scope, scoring rubric, concrete checks, and how to turn findings into a sequenced roadmap with owners.
6 min read
Business Intelligence Slack Bot with AI You Can Verify
How to build a verifiable BI Slack bot: metrics grounding, identity and RLS, clarifying questions, SQL citations, guardrails, formatting, feedback, and a pilot scope.
6 min read
Implementing the dbt Semantic Layer Without Rebuilding Every Metric
A concrete migration plan to implement the dbt Semantic Layer without rewriting every metric: inventory, model entities and grains, define metrics, validate, secure, integrate, and roll out in stages.
10 min read
Data Quality Audit That Produces a Fix List
A practitioner’s playbook to run a data quality audit across your highest-impact data products—and leave with a prioritized 30/60/90‑day remediation plan.
4 min read
Fractional Data Team or Full‑Time Hires: What Fits Now?
A practitioner’s buyer guide comparing fractional data, agencies, and full‑time hires—with concrete scopes, guardrails, and a clean handoff plan.
5 min read
Enterprise Text-to-SQL: What It Takes to Trust the Answer
A practitioner’s guide to shipping enterprise text-to-SQL that answers correctly in production—semantic grounding, approved joins, metrics, permissions, cost controls, and a concrete evaluation plan.
8 min read
dbt Project Audit: What a Useful One Actually Covers
What a real dbt project audit includes, how to do it, and the artifacts you should get back—mapped to severity and a sequenced remediation plan.
7 min read
Upskilling a Data Team on AI Tools That Actually Stick
Why most AI training doesn’t change behavior—and a field-tested format that does. Includes prompt patterns, SQL review norms, and a 90‑day automation plan.
6 min read
Data Team Structure: Who to Hire First, Second, and Third
Centralized vs embedded vs hub-and-spoke, with clear 'pick X if' guidance and the first three hires to make. Practical org patterns from production teams.
9 min read
dbt Mesh: When to Split One Project into Many
When should you split one dbt repo into many? Concrete signals, what breaks in production, and a safe migration path—plus CI, contracts, and ownership.
7 min read
Business Health Dashboard Leaders Actually Open
A practitioner’s plan to build a business health dashboard that leadership actually uses—metrics, piping, dbt models, BI choices, weekly ritual, and failure modes.
7 min read
AI for Data Teams: Workflows That Actually Stick
Which AI workflows actually last past the pilot for a data team? A skeptical, side‑by‑side comparison with code, failure modes, and metrics.
7 min read
Modern Data Stack for Startups: What You Need First
Stage-appropriate picks, plain-English tradeoffs, and real signals for when to add each layer of a modern data stack—without overspending or overbuilding.
10 min read
Analytics Engineering Consultant: What to Ask Before You Hire
A practitioner’s buyer’s guide to hiring an analytics engineering consultant. Learn when to use a consultant vs FTE, how to scope work, evaluate candidates, spot red flags, set timelines, and structure handoff so your team owns the result.
9 min read
Refactoring Legacy SQL in a dbt Project—Without Breaking Reports
Inherited a 600-model repo nobody understands? Here’s the operator’s playbook to refactor legacy SQL in dbt safely, prove parity, and keep BI stable.
4 min read
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