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td-data-profiling

Profile Teradata tables using ClearScape Analytics statistical functions.

7|Updated Dec 3, 2025
Search Tags:#data quality#sql#data profiling#teradata#descriptive statistics#clearscape analytics
One-click install
npx skills add https://github.com/teradata-labs/claude-cookbooks --skill td-data-profiling
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: td-data-profiling
Source: https://github.com/teradata-labs/claude-cookbooks/tree/main/skills/analytics/td-data-profiling
Command: npx skills add https://github.com/teradata-labs/claude-cookbooks --skill td-data-profiling

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the comprehensive data profiling and quality assessment of your Teradata tables, providing deep insights into data characteristics and identifying potential quality issues before they impact analysis or modeling.

Core Features & Use Cases

  • Automated Data Profiling: Generates detailed statistics for numeric and categorical columns.
  • Data Quality Assessment: Identifies missing values, outliers, and inconsistencies.
  • Use Case: Before building a machine learning model, use this Skill to profile your customer dataset. It will reveal missing demographic information, identify unusual transaction amounts, and highlight skewed distributions, guiding your data cleaning and feature engineering efforts.

Quick Start

Profile the table database_name.table_name to understand its data quality.

Frequently Asked Questions about td-data-profiling

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

FAQPage Schema
How do I perform data profiling and quality assessment on Teradata tables?▼

Data profiling on Teradata tables is performed by analyzing univariate statistics, frequency distributions, and data quality metrics. It assesses missing values, outliers, and inconsistencies to reveal potential quality issues before analysis.

What descriptive statistics are generated for numeric and categorical data?▼

Descriptive statistics for numeric and categorical data include univariate statistics, frequency distributions, and correlations. The profiling mechanism highlights skewed distributions and unusual values to guide data cleaning and feature engineering.

Do I need ClearScape Analytics functions to analyze univariate statistics in Teradata?▼

Yes, analyzing univariate statistics requires access to ClearScape Analytics functions like TD_UnivariateStatistics, TD_Frequency, TD_Histogram, TD_ColumnSummary, and TD_Correlation to execute the comprehensive quality assessment.

What's the best way to identify outliers and missing values before building a machine learning model?▼

The best way to identify outliers and missing values is through automated data profiling. It detects unusual transaction amounts and missing demographic information, providing deep insights into data characteristics for feature engineering.

Can I use SQL to detect data quality issues and skewed distributions in my customer dataset?▼

Yes, you can use SQL via Teradata ClearScape Analytics to detect data quality issues and skewed distributions. The profiling mechanism evaluates categorical and numeric columns to uncover inconsistencies directly within your database.

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