skills.rest
emilneuraz-ai
emilneuraz-aiCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

data-quality-frameworks

Enforce data quality across pipelines with Great Expectations, dbt tests, and data contracts.

Updated Apr 4, 2026
Search Tags:#monitoring#data quality#data validation#data pipelines#data contracts#great expectations#dbt tests
One-click install
npx skills add https://github.com/emilneuraz-ai/neuraz-web --skill data-quality-frameworks-emilneuraz-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-quality-frameworks
Source: https://github.com/emilneuraz-ai/neuraz-web/tree/main/.agents/skills/.agents/skills/data-quality-frameworks
Command: npx skills add https://github.com/emilneuraz-ai/neuraz-web --skill data-quality-frameworks-emilneuraz-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Implement data quality validation across data pipelines using Great Expectations, dbt tests, and data contracts to ensure reliable analytics and trustworthy data.

Core Features & Use Cases

  • Setup and manage data quality checks with Great Expectations (expectations, suites, and checkpoints)
  • Validate data with dbt tests and enforce contracts to align schemas and business rules
  • Monitor quality metrics, integrate checks into CI/CD, and enforce data contracts across teams

Quick Start

Create a basic Great Expectations project and define an initial expectation suite to validate core tables.

Frequently Asked Questions about data-quality-frameworks

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

FAQPage Schema
How do I set up data quality checks across my data pipelines?▼

You can set up data quality checks across data pipelines by integrating Great Expectations, dbt tests, and data contracts to validate data from ingestion to downstream analytics, ensuring reliable and trustworthy data.

What is the best way to enforce data contracts between teams?▼

The best way to enforce data contracts is by defining schemas and business rules through dbt tests and contracts, ensuring teams align on data structure and quality standards before data reaches downstream analytics.

Can I run Great Expectations validation in CI/CD?▼

Yes, you can integrate Great Expectations validation into CI/CD pipelines by using checkpoints and expectation suites to automate quality checks and monitor data quality metrics during deployment.

Do I need dbt tests and Great Expectations to validate data ingestion?▼

No, you do not need both, but using dbt tests and Great Expectations together provides comprehensive validation across data pipelines, from schema enforcement during ingestion to complex business rule validation downstream.

How do I create a Great Expectations suite to validate core tables?▼

To create a Great Expectations suite, you start by setting up a basic Great Expectations project and defining an initial expectation suite that specifies the validation rules for your core tables.

Related Skills

Explore More Data & Analytics Skills→
AngelP17AngelP17
1

ml-pipeline-workflow

Automate end-to-end ML pipelines from data ingestion to deployment.

Community
Advanced
mrzhao1277891mrzhao1277891

数据质量专家

Detect and repair crypto data quality issues across multiple timeframes.

Community
Advanced
pluginagentmarketplacepluginagentmarketplace
1

aspnet-core-devops

Containerize ASP.NET Core apps with Docker and deploy to Azure, AWS, or GCP.

Community
Advanced
ivanshamaevivanshamaev
14

data-contracts

Author and validate versioned data contracts with schema, quality checks, and SLAs.

Community
Advanced