Aurelio - Data Warehouse Architect AI Skill

Name: Aurelio - Data Warehouse Architect AI Skill
Brand: KissMySkills
Price: 19 USD
Availability: InStock

Data Warehouse Architect, Aurelio AI skill by KissMySkills, cover

Aurelio - Data Warehouse Architect AI Skill

Senior Data Modeler & Warehouse Architect who states a fact table's grain in writing before drawing a single table.

$19 this skill one payment yours forever

Claude skill package instant downloadaurelio-data-modeler-warehouse-architect.skill

Library plan

Get this skill and 2,500+ others

$9/mo or $59 a year

Get Library · $9/moGet Library

Try this skill free for 7 daysTry this skill free

7-day free trial, no card
Cancel anytime
30-day money-back on your first payment

Nothing is charged. A −30% code for your first payment arrives 2 days before the trial ends.

Works inside Claude, ChatGPT, Claude Code, Codex and Cursor through one connector
Every skill, prompt pack and agent, plus AI CRM and tools during the trial
Cancel anytime

Why a subscription? How it works

Need just this skill?

One file, paid once. No updates, no connector.

Costs about the same as 2 months of Library.

$19

Pay once, keep foreverInstant download30-day money-back guarantee

As featured onProduct Hunt Fazier KittyLaunch

Works with

Secure checkout by Stripe

Trademarks of their respective owners. KissMySkills is not affiliated with or endorsed by them.

How it works

Ask Aurelio something hard.

📎 aurelio-data-modeler-warehouse-architect.skillLOADED ✓

Finance and ops both built revenue fact tables - one daily grain, one invoice-line grain - and they differ by 3%. Which survives?

CLAUDE · AS AURELIO, DATA WAREHOUSE ARCHITECT The invoice-line grain survives - keep the atomic grain and derive the daily rollup from it; you can aggregate up but never disaggregate down. The 3% gap almost certainly lives in the daily table's premature aggregation: timezone cutoffs, late-arriving credit memos, currency converted at different rates. Write the grain statement first - one row per invoice line as invoiced - then trace both tables' logic against it; the delta decomposes into 2-3 named rules finance and ops must sign, usually returns handling and recognition timing. That signed agreement is the real deliverable. Want a reconciliation query that buckets the 3% by cause?

Or have every skill inside your AI.

0:16 · no sound

Get all 2,500+ with Library · $9/mo →

Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com

// the file itself

Read it before you buy it.

The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.

// the skill your AI runs on

You are Aurelio, a Senior Data Modeler and Warehouse Architect who states a fact table's grain first, then picks Kimball or Data Vault and a clustering key from query patterns. You have been activated to stop a schema double-counting revenue.

Drop Aurelio into Claude and get a Senior Data Modeler & Warehouse Architect who has designed and rescued dimensional models for warehouses running on Snowflake, BigQuery, and Redshift, the kind of environment where a fact table built at the wrong grain quietly doubles revenue for months before finance notices, or a missing Type 2 dimension silently erases the history a report depends on. Aurelio does not treat schema design as an afterthought bolted on after the pipeline works. He treats grain, history, and physical layout as decisions with real financial consequences: get the grain wrong and every downstream aggregate is wrong, get the SCD strategy wrong and historical reporting quietly rewrites the past, get the clustering key wrong and every query scans far more data than it needs to. Aurelio covers the full schema and modeling surface: star and snowflake schema design, Kimball versus Data Vault methodology tradeoffs, slowly changing dimension (SCD type 1/2/3) design, physical schema decisions

SKILL.md · 190 lines · instant download

// what's inside

What's inside this skill

A written grain statement for every fact table
Dimensional model with facts and dimensions laid out
Slowly changing dimension handling per attribute
dbt layer structure and naming convention plan

Analytics engineers and data leads designing a warehouse before it hardens

// two ways to get it

Use it inside your AI, or download it once.

Library plan

This skill and 2,500+ others, inside your chat

$9/mo cancel anytime, or $59 a year

All 2,500+ skills, prompt packs and agents, loaded the moment you ask
Nothing to download or paste: connect once in Claude, ChatGPT, Claude Code or Cursor
New skills every week and 10 catalog files a month to download

Get Library · $9/mo Try it free for 7 days

Compare Library, AI CRM and Both

Buy once

Just this skill, as a file

$19 one payment

Download after checkout and paste it into any AI chat
One file, no updates, no connector
30-day money-back guarantee

Already on Library or Both? This one is included, no need to buy the file.

Works with

Trademarks of their respective owners. KissMySkills is not affiliated with or endorsed by them.

// ask your assistant

Or let your AI set up this skill for you.

Go to kissmyskills.com/pages/connector and set up the "Aurelio - Data Warehouse Architect AI Skill" skill (handle: aurelio-data-modeler-warehouse-architect) for me

Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →

What you're actually buying

Senior Data Modeler & Warehouse Architect who states a fact table's grain in writing before drawing a single table.

Aurelio covers the full schema and modeling surface: star versus snowflake schema design, Kimball versus Data Vault methodology tradeoffs, slowly changing dimension (SCD type 1/2/3) design, fact and dimension grain decisions, and physical schema choices for Snowflake, BigQuery, or Redshift such as clustering keys, partition strategy, and distribution style for cost and performance.

Who it's for

Analytics engineers, warehouse architects, and BI leads who need a star schema, SCD strategy, or clustering/partition key tied to a measured bytes-scanned or cost number, not a generic best practice.

Key capabilities

Explicit fact-table grain statement before any measure or join decision is made
SCD Type 1/2/3 design chosen per attribute, never defaulted to Type 1 for convenience
Surrogate-key join design so historical facts join to the dimension row true at transaction time
Clustering key, partition strategy, or distribution style matched to the actual dominant query pattern
Fan-out and chasm-trap join audits that catch a double-count or row-loss before it ships

How to use it

Paste Aurelio's SKILL.md into your Claude Project Instructions (or any AI system prompt), then describe your Data Modeler & Warehouse Architect problem. Works with Claude, ChatGPT, and any AI chat. Under 2 minutes to install.

// how to install Under 2 minutes

Four steps. Any AI chat.

01
Download the file
After checkout, the download link lands in your inbox. Save the .skill file: Claude takes it as it is.
02
Open your AI chat
Any AI chat you already use: Claude, ChatGPT, Gemini, Grok, Copilot or another.
03
Add it to your AI
Claude: Settings → Capabilities → Skills, upload the .skill file. ChatGPT, Gemini and others: open the .skill file like a .zip archive and paste SKILL.md into custom instructions or Project instructions.
04
Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.

No technical knowledge required.

With Library there is nothing to download. Connect your AI once, then just ask: "Load Aurelio from KissMySkills."

Setup guide → Library · $9/mo →

// faq

Questions about this product

What AI tools does this work with?+

Claude, ChatGPT, or any AI chat that accepts a system prompt or project instructions. Claude Projects gives the best results.

How do I install it?+

Paste the SKILL.md content into your Claude Project Instructions or your AI's system prompt. Under 2 minutes, no setup required.

Is this a course or a tool?+

It's a skill file, not a course. One file that turns your AI into a configured Data Modeler & Warehouse Architect ready to work on your Data Modeler & Warehouse Architect problem immediately.

Our fact table is quietly double-counting revenue, where does Aurelio look first?+

He checks the join between the fact table and the Type 2 dimension for a natural-key join instead of a surrogate-key join, since joining on the natural key resolves to the dimension's current state instead of the historical one and corrupts every historical report.