td-outlier-detection
OfficialDetect and handle outliers in your data.
Data & Analytics#data quality#preprocessing#anomaly detection#teradata#outlier detection#td_outlierfit
Authorteradata-labs
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill automates the process of identifying and handling outliers in your Teradata datasets, improving data quality and the reliability of your analyses.
Core Features & Use Cases
- Automated Outlier Detection: Leverages Teradata's TD_OutlierFit function to find anomalies.
- Data Quality Improvement: Prepares data for more accurate modeling by addressing outliers.
- Use Case: Automatically scan your customer transaction data to identify and flag unusual spending patterns that might indicate fraud or data entry errors.
Quick Start
Analyze table: my_database.my_transactions with target column: transaction_amount.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: td-outlier-detection Download link: https://github.com/teradata-labs/claude-cookbooks/archive/main.zip#td-outlier-detection Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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