td-data-preparation

What problem does it solve?

This Skill automates the complex process of preparing raw time series data, ensuring it's clean, validated, and optimally formatted for Teradata's Unbounded Array Framework (UAF) analytics functions.

Core Features & Use Cases

• Data Validation: Checks for missing timestamps, duplicate entries, and identifies outliers.
• Time Series Formatting: Standardizes temporal data and extracts relevant features (year, month, day, etc.).
• Missing Value Imputation: Fills gaps using methods like forward fill or linear interpolation.
• Use Case: Prepare sensor data from millions of IoT devices for advanced time series forecasting models within Teradata Vantage.

Quick Start

Prepare the time series data in the 'my_database.sensor_readings' table with timestamp column 'event_time' and value column 'temperature'.