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demo-dataquality-metrics

Monitor Snowflake dataset quality with Data Metric Functions and Streamlit dashboards.

3|1|Updated Mar 2, 2026
Search Tags:#data quality#dashboard#Streamlit#Snowflake#data monitoring#DMFs
One-click install
npx skills add https://github.com/sfc-gh-miwhitaker/sfe-public --skill demo-dataquality-metrics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: demo-dataquality-metrics
Source: https://github.com/sfc-gh-miwhitaker/sfe-public/tree/main/_archive/demo-dataquality-metrics/.claude/skills/demo-dataquality-metrics
Command: npx skills add https://github.com/sfc-gh-miwhitaker/sfe-public --skill demo-dataquality-metrics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the challenge of maintaining high data quality across large datasets by providing automated monitoring and reporting.

Core Features & Use Cases

  • Automated Data Quality Monitoring: Uses Snowflake Data Metric Functions (DMFs) to track quality in real-time.
  • Custom DMFs: Enables users to create and apply custom DMFs for domain-specific validations.
  • Streamlit Dashboard: Offers a user-friendly interface for viewing quality scores, trends, and system DMFs.
  • Use Case: Ideal for sports analytics teams looking to track athlete performance and fan engagement metrics.

Quick Start

Deploy the demo-dataquality-metrics skill to start monitoring data quality for your dataset.

Frequently Asked Questions about demo-dataquality-metrics

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

FAQPage Schema
How do I monitor data quality in Snowflake using Data Metric Functions?▼

You can monitor Snowflake data quality by applying Data Metric Functions to track quality scores automatically. This Skill automates DMF computation and provides real-time visibility into dataset health metrics.

Can I create custom data quality metrics for domain-specific validations?▼

Yes, you can create and apply custom Data Metric Functions for domain-specific data quality validations. This allows you to track specialized metrics tailored to your specific dataset requirements.

Do I need Streamlit installed to visualize Snowflake data quality dashboards?▼

Yes, Streamlit is required to visualize the data quality dashboards. The Skill uses Streamlit to provide a user-friendly interface for viewing quality scores, trends, and system DMFs.

How do I track athlete performance and fan engagement metrics using data monitoring?▼

You can track athlete performance and fan engagement metrics by deploying this data monitoring Skill. It automates the computation of quality metrics to ensure your sports analytics datasets remain accurate.

What is needed to set up automated data quality monitoring in a Snowflake environment?▼

Setting up automated data quality monitoring requires a Snowflake environment with Data Metric Functions enabled and Streamlit installed. This configuration allows the Skill to compute metrics and display dashboards.

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