Data & Analytics Skill
Airflow DAG Patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and…
$15
Data
Analytics and data query patterns for metrics, dashboards, reports, KPIs, and funnel analysis
A library of analytics and reporting query patterns for the metrics that matter: active users, growth, retention cohorts, funnels, and revenue. It pairs ready-to-adapt SQL with an event-tracking schema and dashboard components, so you can stand up reliable KPIs and visualizations instead of writing aggregation logic from scratch.
$15 one-time
Add to a kit → Prices include 20% VAT. · Forged on real agency work · one-time, no lock-in
- Type Skill
- Category Data & Analytics
- Delivery Email · instant
- License One-time
Inside the run · no black box
See the actual work before you buy it.
Every dashboard here starts from a question, not a table. The skill writes the metric SQL precisely, wires funnels and revenue views into single queries, and indexes the hot paths before anything slows down.
- Starts the schema from the question, not the table: how will this data be queried decides the design, then defends it in layers with RLS, app-level auth and input validation.
- Defines the core metric SQL precisely instead of vaguely: DAU, WAU, MAU and the stickiness ratio, week-over-week growth with window functions, and cohort retention that tracks each signup week across its following weeks.
- Builds the conversion funnel as one query: distinct users counted at each step from page view to purchase, step-to-step percentages plus overall conversion, so the leak point is visible in a single table.
- Covers the revenue side with MRR by month, ARPU per paying user and LTV with both average and median, because a few whales distort the average and the median tells the honest story.
- Ships a typed event tracking schema: every event carries an id, name, user and anonymous id, timestamp, properties and context including UTM campaign data, sent through one track() implementation rather than scattered calls.
- Optimizes before the dashboard slows down: composite indexes on the common query paths, expensive aggregations moved into materialized views refreshed daily, and closes with the checklist of retention policy and privacy compliance.
One power source. 6 lines out.
data · core
core active · 6 lines
- ✓ calculating active users
Calculating active users (daily, weekly, monthly) and stickiness ratios
- ✓ building cohort retention
Building cohort retention and week-over-week growth analyses
- ✓ measuring a multi-step c…
Measuring a multi-step conversion funnel from visit to purchase
- ✓ computing revenue metrics:
Computing revenue metrics: recurring revenue, revenue per user, lifetime value
- ✓ defining a structured an…
Defining a structured analytics event schema for client-side tracking
- ✓ optimizing slow aggregat…
Optimizing slow aggregation queries with indexes and materialized views
Yours to keep.
Drag time forward. Watch what stays.
Forever
That's what owning means.
The rented stack
ai writing tool: subscription
expired · access lostanalytics suite: subscription
expired · access lostdesign platform: subscription
expired · access lost(nothing left)
Your forge
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Stand up trustworthy KPI dashboards quickly with proven query patterns instead of guesswork
license: perpetual -
Spot retention and funnel leaks early with cohort and step-conversion analyses
license: perpetual -
Keep dashboards fast under load through indexed queries and materialized aggregations
license: perpetual -
Track product behavior consistently with a well-structured event schema
license: perpetual
subscriptions expire · deeds don't
Everything in the box.
Pick a piece up. Watch it work.
User-metric queries for active users, stickiness, signups, and growth rate
6 parts · one working system · ships instantly by email
This wasn't forged for everyone.
- Not for you if you'd rather rent a tool than own one.
- Not for you if you want someone else to run your stack.
- Not for you if you're happy guessing.
Developers and analysts building metric dashboards, KPI reports, and funnel analyses on a SQL data store.
then this was forged for you.Works with
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.
- Claude Native format
- ChatGPT Adapts via open standards
- Gemini Adapts via open standards
- Cursor Adapts via open standards
- Copilot Adapts via open standards
Catch what's on your mind.
the air is clear. nothing between you and the forge.
catch a spark: the forge will answer
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These are SQL patterns. Do they assume a specific database, or do I adapt them to mine?
They are written as ready-to-adapt SQL, so you fit them to your own data store rather than expecting a one-click connector. Most patterns lean on standard SQL, with the table and column names swapped for yours.
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How much rework before these queries run on my actual schema?
The shape of each query, the metric logic for active users, cohorts, or funnels, is the part you keep, while the table and event names are what you change. The event-tracking schema it ships shows the structure these queries expect.
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Does it set up the tracking, or assume the data is already there?
It queries data you are already capturing and gives you a schema to model events against, but it does not collect the events for you. If the underlying tracking is not in place, those metrics have nothing to read.
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How is it delivered?
By email right after purchase: ready to run, downloaded instantly, no setup wait.
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One-time or subscription?
A one-time purchase; no subscription or hidden fees. VAT (20%) is included.
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Can I get a refund?
As a digital product, it can’t be refunded once downloaded. That’s why we show exactly what’s inside and who it’s for, right here.