---
name: fabric-model-19c2f9166d31
description: Build Gold layer analytical objects — dimensional models (Kimball star schema), KPI aggregates, wide tables, or TMDL semantic models. Use when creating fact tables, dimension tables, monthly aggregates, or Power BI semantic models from Silver data. Enforces referential integrity, metric standardization, and schema locking.
---

# fabric-model

## MUST

- Define business metrics in Gold — never in the BI tool or downstream
- Verify dimension key existence before writing fact rows (referential integrity gate)
- Link orphan facts to the `-1` / `Unknown` dimension key — never drop fact rows
- Run `OPTIMIZE` with `ZORDER` after every Gold write
- Gold schemas are a contract — schema changes require explicit approval and backfill plan

## PREFER

- Kimball star schema (fact + dimension tables) for standard reporting
- One atomic fact table at lowest grain + aggregate tables for KPIs
- Delta Lake tables over views for materialized Gold
- Separate lakehouse for Gold layer (independent access control)
- `DELETE + INSERT` over MERGE in Fabric Warehouse (MERGE is preview)

## AVOID

- Business logic (churn definition, LTV formula) in Power BI DAX — define it in Gold
- Dropping fact rows when dimension is missing — use Unknown dimension key
- Plain APPEND on Gold tables (creates duplicates on re-run)
- Overloading fact tables with descriptive attributes (put them in dimensions)

## Dimensional Model Pattern

```python
# Dimension table (slowly changing, type 1 overwrite)
dim_customers = silver_customers.select(
    F.col("customer_id"),
    F.col("customer_name"),
    F.col("region"),
    F.col("segment"),
    F.current_timestamp().alias("_dim_updated_at"),
).dropDuplicates(["customer_id"])

(dim_customers.write
    .format("delta")
    .mode("overwrite")
    .option("overwriteSchema", "false")  # schema is locked
    .save(dim_path)
)

# Fact table with RI gate
unknown_customer_id = -1

fact_orders = (silver_orders
    .join(dim_customers.select("customer_id"), on="customer_id", how="left")
    .withColumn("customer_key",
        F.when(F.col("customer_id").isNotNull(), F.col("customer_id"))
         .otherwise(F.lit(unknown_customer_id))
    )
)

(fact_orders
    .write.format("delta")
    .mode("overwrite")
    .partitionBy("order_month")
    .save(fact_path)
)
```

## Gold Optimization (always run after write)

```python
spark.conf.set("spark.sql.parquet.vorder.enabled", "true")
spark.conf.set("spark.microsoft.delta.optimizeWrite.enabled", "true")
spark.sql(f"OPTIMIZE delta.`{fact_path}` ZORDER BY (order_date, region_id)")
```

## KPI Aggregate Pattern

```python
kpi_monthly = (fact_orders
    .groupBy(
        F.date_format("order_date", "yyyy-MM").alias("month"),
        F.col("region_id")
    )
    .agg(
        F.sum("revenue").alias("total_revenue"),
        F.countDistinct("customer_id").alias("active_customers"),
        F.count("order_id").alias("order_count"),
    )
)
```


---
Source attribution: scardoso-lu
Original project: https://github.com/scardoso-lu/fabric-skills-settings/blob/33534eb185fda573125308a0129457bd65419d13/server/skills/fabric-model/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Silvio Cardoso

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: scardoso-lu
Original project: https://github.com/scardoso-lu/fabric-skills-settings/blob/33534eb185fda573125308a0129457bd65419d13/server/skills/fabric-model/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Operations, Product Management
Roles: Business Process Analyst, Data Analyst, Data Scientist, Growth Product Manager, Product Manager
Specialties: API, Database
Tools: Delta Lake, Power Bi
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 48a6ac8835653e7d70b72430cfc3e98c99a99e85e8558a260a18d75c8d9394f5