skills.rest
duggal1
duggal1COMMUNITY
Explore all skills by this author →
Website𝕏@harshitduggal5GitHub

data-quality-framework

Automate data quality verification across pipelines with Great Expectations and dbt tests.

2|1|Updated Mar 8, 2026
Search Tags:#validation#data-quality#great-expectations#data-profiling#data-contract#dbt-tests
One-click install
npx skills add https://github.com/duggal1/Sapphire-cli --skill data-quality-framework-duggal1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-quality-framework
Source: https://github.com/duggal1/Sapphire-cli/tree/main/skills/data-pipeline/.claude/skills/data-quality-framework
Command: npx skills add https://github.com/duggal1/Sapphire-cli --skill data-quality-framework-duggal1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data quality issues across data pipelines can lead to wrong decisions and operational risk; this framework provides structured rules and monitoring to detect and prevent inaccuracies, gaps, and delays.

Core Features & Use Cases

  • Define verification rules for accuracy, completeness, timeliness, and consistency.
  • Integrate with Great Expectations and dbt tests to validate data and trigger alerts.
  • Use data profiling and data contracts to document expectations and enforce governance.

Quick Start

Create a starter data-quality framework with defined rules for accuracy, completeness, and timeliness and run it against a sample dataset.

Frequently Asked Questions about data-quality-framework

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

FAQPage Schema
How do I automate data-quality checks across my pipelines?▼

A data quality framework defines verification rules for accuracy, completeness, timeliness, and consistency, using a YAML ruleset and data contracts to detect and prevent inaccuracies, gaps, and delays.

Can I integrate data quality validation with Great Expectations and dbt tests?▼

You can integrate validation points for Great Expectations and dbt tests to validate data accuracy and trigger alerts, governed by data contracts describing schemas and quality criteria.

What is a data contract and how does it enforce data quality?▼

A data contract is a snippet describing schemas and quality criteria that enforces data quality by documenting expectations and applying validation rules for accuracy and completeness.

How do I run data profiling to monitor pipeline accuracy and completeness?▼

Data profiling monitors pipeline accuracy and completeness by applying a YAML ruleset of verification rules to sample datasets, validating expectations before operationalizing the pipeline.

Do I need a YAML ruleset to define data quality verification rules?▼

A YAML ruleset is required to define structured verification rules for accuracy, completeness, timeliness, and consistency, which are then applied to validate your data pipelines.

Related Skills

Explore More Data & Analytics Skills→
nahisahonahisaho
3

scientific-data-profiling

Profile datasets with ydata-profiling and Great Expectations to generate EDA reports and quality scores.

Community
Advanced
ekremmkasapekremmkasap

data-quality-frameworks

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

Community
Advanced
haxlyshaxlys

data-quality-frameworks

Validate data quality with Great Expectations, dbt tests, and data contracts.

Community
Advanced
JaviMontanoJaviMontano

metodologia-data-quality

Design a data quality framework for profiling, validation, anomaly detection, contracts, and SLA monitoring.

Community
Advanced