Airflow DAG Patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and…
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A complete methodology for designing KPI dashboards that drive decisions, not just display numbers. It covers metric selection, a strategic-to-operational hierarchy, visualization best practices, and ready layouts for executive, SaaS, and real-time operations views, backed by SQL and Streamlit implementation code.
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Inside the run · no black box
Out of dozens of available metrics, only 5 to 7 survive. Each one gets an audience, a target and a pyramid layer before any chart is drawn, and color always means position against the SLO.
kpi-dashboard-design · core
core active · 6 lines
Designing an executive summary dashboard with headline KPIs and trends
Building a SaaS metrics view with MRR, unit economics, and cohort retention
Creating real-time operations dashboards with system health and service status
Selecting the right 5-to-7 KPIs from dozens of candidate metrics
Writing SQL for MRR, cohort retention, and customer acquisition cost
Improving cluttered existing dashboards for clarity and mobile use
Drag time forward. Watch what stays.
Forever
That's what owning means.
ai writing tool: subscription
expired · access lostanalytics suite: subscription
expired · access lostdesign platform: subscription
expired · access lost(nothing left)
Drive faster decisions by leading with the result, then the supporting detail
license: perpetualCut visual noise by focusing on the highest-impact metrics, not every number
license: perpetualGive every metric meaning by showing it against targets, trends, and context
license: perpetualBuild dashboards people actually read with fast load times and clear hierarchy
license: perpetualsubscriptions expire · deeds don't
Pick a piece up. Watch it work.
KPI hierarchy framework spanning strategic, tactical, and operational levels
6 parts · one working system · ships instantly by email
Data analysts, product managers, and operators who design business dashboards and want metrics that lead to action instead of clutter.
then this was forged for you.Universal by design: these run in any AI. Delivered in the open Agent Skills + MCP format (native in Claude); ChatGPT, Gemini, Cursor and Copilot adapt the same files their own way.
No. The core of the methodology is tool-agnostic: the KPI hierarchy, metric selection, and layout patterns apply identically in Tableau or Looker. The SQL templates for MRR, cohort retention, and acquisition cost run on whatever database sits underneath, and the Streamlit code is just one reference implementation.
Through the hierarchy: metrics split into strategic, tactical, and operational levels, and each view commits to one level with 5 to 7 KPIs. Every metric is shown against targets, trends, and context, with the result leading and the detail following. The department catalogs help you cut vanity metrics early.
No. It's a design methodology with templates, not an ETL tool. The SQL runs on data you already have in a queryable store; moving the data there is separate engineering work.
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