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profiling-tables

Analyze a specified table to generate a structured data profile.

419|61|Updated Jan 13, 2026
Search Tags:#SQL#statistics#data-quality#profile#cardinality#information_schema
One-click install
npx skills add https://github.com/astronomer/agents --skill profiling-tables
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: profiling-tables
Source: https://github.com/astronomer/agents/tree/main/skills/profiling-tables
Command: npx skills add https://github.com/astronomer/agents --skill profiling-tables

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps data teams quickly understand a table's structure, size, statistics, and quality, enabling trust and faster data-informed decisions.

Core Features & Use Cases

  • Table metadata discovery: Retrieve schema, table name, row counts, and basic statistics.
  • Column-level profiling: Compute data-type specific statistics for numeric, string, and date columns; identify data quality issues.
  • Use Case: On onboarding a new dataset, generate a data dictionary and quality checks to guide downstream analytics.

Quick Start

Profile the table sales.public_transactions to generate a full data profile for immediate analysis.

Frequently Asked Questions about profiling-tables

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

FAQPage Schema
How do I profile a table's structure and data quality in a data warehouse?▼

Table profiling analyzes a specified table to generate a comprehensive data profile, retrieving schema metadata from INFORMATION_SCHEMA, computing row counts, and calculating column-level statistics to assess data quality.

What statistics are included when profiling SQL table columns?▼

SQL table profiling computes data-type specific statistics for numeric, string, and date columns, calculating cardinality and identifying data quality issues to generate a structured summary for analysis.

Can I generate a data dictionary by retrieving metadata from INFORMATION_SCHEMA?▼

Yes, table profiling retrieves schema, table names, and basic statistics from INFORMATION_SCHEMA, enabling you to generate a data dictionary and quality checks to guide downstream analytics.

What is the best way to understand cardinality and row counts for a new dataset?▼

The best way to understand cardinality and row counts is table profiling, which fetches metadata, computes row counts, and analyzes column-level statistics to produce a structured summary for immediate analysis.

Does table profiling require any dependencies to compute column statistics?▼

No, table profiling has no dependencies and directly queries the warehouse to compute data-type specific column statistics, cardinality, and data quality metrics for the specified table.

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