td-powerspec

Analyze time series data with Teradata TD_PowerSpec in the Unbounded Array Framework.

7|Updated Dec 3, 2025

Search Tags:#time series #signal processing #frequency analysis #UAF #Teradata #power spectrum

Ready to run

npx skills add https://github.com/teradata-labs/claude-cookbooks --skill td-powerspec

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: td-powerspec
Source: https://github.com/teradata-labs/claude-cookbooks/tree/main/skills/analytics/td-powerspec
Command: npx skills add https://github.com/teradata-labs/claude-cookbooks --skill td-powerspec

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the complex process of power spectrum analysis on time series data, enabling users to detect underlying frequencies, periodicities, and seasonality without deep expertise in signal processing or the Teradata Unbounded Array Framework (UAF).

Core Features & Use Cases

Power Spectrum Analysis: Computes the power spectral density of time series data to identify dominant frequencies.
Periodicity Detection: Helps uncover cyclical patterns and hidden periodicities within your data.
UAF Integration: Leverages Teradata's Unbounded Array Framework for scalable and efficient processing of large datasets.
Use Case: Analyze sensor data from industrial machinery to detect vibrations at specific frequencies that might indicate an impending failure.

Quick Start

Analyze the power spectrum of the 'sensor_data' table in the 'my_database' database using the 'timestamp_col' and 'value_col'.

Frequently Asked Questions about td-powerspec

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

FAQPage Schema

How do I perform power spectrum analysis on time series data in Teradata?▼

Power spectrum analysis on time series data is executed using Teradata's TD_PowerSpec function within the Unbounded Array Framework to compute power spectral density and identify dominant frequencies. This requires a Teradata Vantage environment with UAF enabled.

What is power spectrum analysis used for in signal processing and IoT data?▼

Power spectrum analysis is used in signal processing and IoT data to identify underlying frequencies, periodicities, and seasonality. It helps detect cyclical patterns, such as analyzing industrial machinery sensor data to find vibrations indicating impending failure.

Do I need specific licensing to use TD_PowerSpec for frequency domain analysis?▼

Yes, you need appropriate licensing for TD_PowerSpec to perform frequency domain analysis. Additionally, your environment must be running Teradata Vantage with the Unbounded Array Framework (UAF) enabled to execute the power spectrum calculations.

Can I detect seasonality and periodicity in financial time series using Teradata Vantage?▼

You can detect seasonality and periodicity in financial time series using Teradata Vantage by leveraging the TD_PowerSpec function. This approach computes the power spectral density to uncover hidden cyclical patterns and dominant frequencies within large financial datasets.

How do I analyze sensor data for dominant frequencies in a Teradata database?▼

To analyze sensor data for dominant frequencies, you run the TD_PowerSpec function on your time series table within the Unbounded Array Framework. This requires specifying the database, table, timestamp column, and value column to compute the power spectrum.