skills.rest
accelerate-data
accelerate-dataOFFICIAL
Explore all skills by this author →
WebsiteGitHub

elementary-data-quality

Automate anomaly detection and schema validation for Microsoft Fabric data quality monitoring.

Updated Mar 16, 2026
Search Tags:#data quality#dbt#anomaly detection#Microsoft Fabric#Elementary
One-click install
npx skills add https://github.com/accelerate-data/vibedata-official --skill elementary-data-quality
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: elementary-data-quality
Source: https://github.com/accelerate-data/vibedata-official/tree/main/plugins/vibedata-dbt-skills/skills/elementary-data-quality
Command: npx skills add https://github.com/accelerate-data/vibedata-official --skill elementary-data-quality

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires dbt, elementary-data, dbt-msft/tsql_utils, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of ensuring data quality and anomaly detection on Microsoft Fabric, leveraging dbt and Elementary for streamlined data observability.

Core Features & Use Cases

  • Data Quality Testing: Implement comprehensive anomaly detection and schema tests to monitor data integrity.
  • Layered Testing Strategy: Apply targeted tests across Bronze, Silver, and Gold layers to catch issues early and protect data quality.
  • Volume and Column Anomalies: Detect unexpected changes in data volume and column metrics, including missing data, outliers, and schema drift.
  • Schema Changes: Monitor schema changes to ensure consistency with business logic and downstream systems.
  • Use Case: For a new data pipeline on Fabric, this Skill can automatically set up and maintain a robust data quality monitoring system, alerting on issues before they impact critical business processes.

Quick Start

Install the elementary-data-quality skill using Claude Code:

/plugin install elementary-data-quality@vibedata-dbt-skills

Frequently Asked Questions about elementary-data-quality

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate data quality checks and anomaly detection on Microsoft Fabric?▼

Automate data quality checks on Microsoft Fabric by leveraging dbt and Elementary to enforce standards, detect schema drift, and monitor anomalies across bronze, silver, and gold data layers.

What is the best way to monitor schema changes and data volume anomalies in dbt?▼

Monitor schema changes and volume anomalies in dbt by applying targeted tests across data layers to catch missing data, outliers, and schema drift before impacting downstream systems.

Does the Elementary anomaly detection Skill require dbt-msft/tsql_utils?▼

Yes, Elementary anomaly detection on Fabric requires dbt, elementary-data, and the dbt-msft/tsql_utils package to execute schema validation and data observability workflows.

Can I apply layered data testing strategies across bronze, silver, and gold layers in Fabric?▼

Yes, you can apply a layered testing strategy across bronze, silver, and gold layers in Fabric to catch data integrity issues early and protect critical business processes.

How do I set up data observability for a new pipeline on Microsoft Fabric?▼

Set up data observability for a new Fabric pipeline by configuring schema tests and anomaly detection with dbt and Elementary to automatically alert on unexpected volume or column metric changes.

What type of column anomalies can Elementary detect on Fabric?▼

Elementary detects unexpected changes in column metrics, including missing data, outliers, and schema drift, ensuring data consistency with business logic and downstream systems.

Related Skills

Explore More Data & Analytics Skills→
EngineerWithAIEngineerWithAI
4

data-quality-frameworks

Implement data quality validation frameworks using Great Expectations, dbt tests, and data contracts.

Official
Advanced
nrakownrakow
1

anomaly-detection

Automate anomaly detection in dbt data pipelines for volume, freshness, and distribution issues.

Community
Advanced
nrakownrakow
1

data-quality-testing

Generate and implement dbt tests for schema, SQL, and anomaly monitoring.

Community
Advanced
armanzeroeightarmanzeroeight
29

test-generator

Generate schema, data quality, and freshness tests for dbt models.

Community
Intermediate