Teradata Labs
Official@teradata-labs
Offers advanced SQL-based analytics, time series forecasting, and workload management capabilities for enterprise-scale data systems and ClearScape Analytics environments.
Agent Skills by Teradata Labs
Showing 63 vetted skills indexed across 1 GitHub repositories.
tune-workloads
Analyze and configure Teradata workload classification rules, filters, and priorities via MCP tools.
optimize-throttles
Analyze Teradata throttle behavior and configure optimal settings via MCP tools.
analyze-performance
Analyze throttle statistics, query logs, and resource metrics to identify performance bottlenecks.
monitor-workloads
Monitor Teradata workload definitions, query distribution, and TASM statistics.
monitor-resources
Monitor Teradata AMP processor load, CPU, memory, and I/O utilization in real-time.
monitor-sessions
Monitor active Teradata sessions to identify performance issues and blocking.
monitor-queries
Monitor Teradata query execution with real-time resources and historical logs.
control-sessions
Identify and terminate problematic database sessions using MCP tools.
manage-workloads
Automate creation and management of Teradata workload filters, throttles, and classification rules.
manage-queues
Manage delayed Teradata request queues by releasing or aborting blocked requests.
td-window
Generate Teradata UAF SQL workflows using the TD_WINDOW function for signal windowing.
td-svm
Build and deploy SVM classification models using Teradata ClearScape Analytics TD_SVM.
td-ngram-splitter
Generate unigrams, bigrams, and trigrams from text using Teradata Vantage.
td-linear-regression
Build and deploy linear regression models with Teradata ClearScape Analytics TD_LinearRegression.
td-hierarchical-clustering
Perform hierarchical clustering on Teradata Vantage with SQL generation.
td-diff
Apply Teradata TD_DIFF differencing to time series data within the Unbounded Array Framework.
td-cross-validation
Perform time series cross-validation using Teradata UAF TD_CROSS_VALIDATION.
td-logistic-regression
Build and deploy logistic regression models using Teradata's TD_LogisticRegression function.
td-powerspec
Analyze time series data with Teradata TD_PowerSpec in the Unbounded Array Framework.
td-smoothing
Smooth time series data using Teradata's TD_SMOOTHING function and UAF.
td-fft
Performs Fast Fourier Transform analysis on time series data using Teradata's UAF TD_FFT function.
td-change-point
Detect structural breaks and regime changes in time series using Teradata's TD_CHANGE_POINT function.
td-decision-tree
Automate TD_DecisionTree classification model creation and deployment in Teradata Vantage.
td-movavg-forecast
Generate moving average forecasts for time series data using Teradata UAF.
Frequently Asked Questions About Teradata Labs
FAQPage SchemaWhat specific tasks can I perform using these Teradata Labs capabilities?▼
You can manage database workload performance, execute advanced time series analysis, and build predictive models. Capabilities include session monitoring, resource utilization tracking, signal processing, and deploying statistical models like linear regression or decision trees directly within the database environment.
Who is the target persona for these database and analytics functions?▼
These functions are designed for database administrators, data engineers, and data scientists working within Teradata Vantage environments. They enable technical teams to perform in-database feature engineering, model evaluation, and system performance tuning without moving large datasets to external processing environments.
What are the prerequisites for running these analytical functions?▼
These functions require an active Teradata Vantage instance with ClearScape Analytics enabled. Users must have appropriate database permissions to execute UAF functions and manage workload definitions, as these operations interact directly with the database engine and system resource management layers.