Analyze an A/B test experiment and provide a clear ship/iterate/no-ship recommendation. Use when evaluating experiment results.
Run correlation analysis on connected data, identify strong relationships, and suggest regression models. Use when exploring relationships between variables.
Discover natural groupings in data using clustering algorithms with evaluation and visualization. Use when segmenting data or finding patterns.
Run an end-to-end data analysis pipeline — connect, profile, analyze, and report. Use when performing a complete analysis workflow.
Connect to a data source, profile its schema and quality, and recommend appropriate analyses. Use when starting work with a new dataset.
Analyze a time series and generate forecasts with confidence intervals. Use when predicting future values from historical data.
Explore a graph or network dataset — structure, statistics, paths, and visualization. Use when working with DOT, GML, GraphML, or Mermaid files.
Build and evaluate regression models to predict a target variable. Use when modeling relationships between features and an outcome.