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
Field notes on analytics engineering
What we learn shipping dbt migrations, tuning slow repos, hardening Airflow, and pointing AI agents at production data. Written by practitioners, for practitioners.
Anomaly Detection for Data Pipelines Without Alert Fatigue
A practitioner’s guide to data anomaly detection that teams actually trust. Concrete methods, code, and routing to cut noise and catch real breaks.
9 min read
SQL Query Optimization for Columnar Warehouses
Triage and fix slow queries on Snowflake and BigQuery. Read profiles, prune data, control joins, avoid spill, and rewrite windows—backed by production patterns.
5 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
Airflow Monitoring That Warns You Before Users Do
What to actually monitor in Airflow, with concrete queries, configs, and alert routing that find problems before users do—plus real data freshness checks.
6 min read
Airflow + dbt: Run dbt From Airflow With Model-Level Visibility
A practitioner’s guide to running dbt from Airflow with model-level visibility. Compare Bash, dbt Cloud API, Cosmos, and Kubernetes—with real code and trade-offs.
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
dbt Materializations: View, Table, Incremental, Ephemeral
A decision framework for dbt materializations that holds up in production: cost math, when views beat tables, incremental pitfalls, ephemeral tradeoffs, and safe swaps.
5 min read
Internal AI Platform Architecture: Connect Agents to Your Stack
A practitioner’s guide to architecting an internal AI platform that safely connects Slack agents to GitHub, Jira, Linear, Notion, Snowflake, and more—with approvals, evals, and cost controls.
8 min read
Airflow DAG Not Running: A Systematic Debugging Path
Your DAG isn’t firing and the clock is ticking. Use this ordered decision tree—commands, log paths, and configs included—to isolate and fix the cause fast.
3 min read
dbt CI/CD That Catches Problems Before They Reach Prod
A complete dbt CI/CD pipeline that builds only what changed, isolates writes in a temporary schema, lints first, and blocks bad merges—plus real GitHub Actions YAML.
5 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
Building a Slack AI Agent That Can Actually Query Your Warehouse
A practitioner’s guide to shipping a Slack AI agent that runs real warehouse queries—scoped, grounded on dbt, cost-safe, and evaluated for drift.
7 min read
dbt Cloud Pricing: What It Actually Costs in 2026
Seat vs. consumption costs, the real trade‑offs with self‑hosting, and a break‑even model you can plug your own numbers into—no fluff, just operator detail.
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
Managed Airflow Compared: MWAA vs Astronomer vs Composer
A practitioner comparison of MWAA, Astronomer, and Cloud Composer—with upgrade cadence, scaling, observability, pricing, and clear pick‑X‑if guidance.
6 min read
Airflow Best Practices From Someone Who's Been Paged at 3am
Reliability-first Airflow guidance from production incidents: idempotency, retries, deferrable sensors, SLAs, secrets, CI tests, and MWAA/Astronomer/Composer nuances.
9 min read
dbt Incremental Models: Strategies That Hold Up in Prod
A practitioner’s guide to dbt incremental models: when to use them, how to configure them, and how to avoid the production failures teams learn the hard way.
9 min read
dbt Cloud Migration: Move Without Breaking Production
A practitioner’s playbook to move from dbt-core on Airflow/cron to dbt Cloud with zero surprises: cost, fit, mapping, Slim CI, parity, cutover, and rollback.
5 min read
Snowflake Cost Optimization: Where the Credits Go
A practitioner’s guide to Snowflake cost optimization: attribute spend, fix warehouse settings, prune scans with clustering/MVs, and prevent regressions.
5 min read
dbt run slow? Why it happens and 7 fixes that work
If your dbt run is slow, start with the critical path: run_results.json, model timing, and the DAG’s longest chain. Then apply the seven fixes that actually pay off.
7 min read
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