Skill UI

Provides comprehensive monitoring for the Clay data enrichment pipeline. It tracks critical operational metrics such as credit consumption velocity, enrichment success rates (hit rates), data quality scores, and lead distribution. Essential for cost control and ensuring pipeline health in data-intensive CRM workflows.

Builds AutoML pipelines by analyzing user requests, generating code for data preparation, model selection, hyperparameter tuning, validation, and metrics, then documenting artifacts for streamlined automated machine learning workflows.

Automates cohort analysis creation by offering step-by-step analytics guidance, SQL patterns, visualization advice, and validation so analysts can produce production-ready insights within data analytics workflows.

Provides automated, industry-standard guidance and code for complex SQL joins, visualizations, and BI analyses whenever the “complex join helper” skill is invoked in a data analytics context.

Automates correlation analyzer workflows by offering best-practice guidance, executable SQL, visualization tips, and statistical validation for data analytics requests.

Automates common CTE query builder tasks for data analytics, offering best-practice guidance, production-ready SQL snippets, and validation against standard requirements when you need help with BI, visualization, or statistical analysis.

Automates dashboard layout planning for data analytics tasks, guiding best practices, generating robust configs, and validating layouts for SQL-driven BI scenarios.

This skill models the expertise of a senior data scientist, covering the entire data science lifecycle. It provides advanced capabilities in statistical modeling, machine learning (deep learning, XGBoost), predictive analytics, and business intelligence. From raw data exploration (EDA) to deploying production-ready models and creating actionable dashboards, it covers technical depth across Python, R, SQL, and cloud platforms, while applying domain knowledge in finance, marketing, and operations.

Automates the data story outlining process for analytic workflows, offering guidance on SQL, visualization, statistics, and BI so teams can structure insights consistently.

This comprehensive diagnostic bundle collects critical evidence from the Databricks environment, including environment setup, cluster state, job run history, and Delta table diagnostics. It generates a redacted, safe tar.gz file specifically designed for submitting detailed support tickets and efficiently troubleshooting complex data pipeline issues.

A comprehensive guide to implementing best practices for security within Databricks. Learn how to manage secrets using scoped storage, enforce the principle of least privilege via Unity Catalog grants, audit API tokens, and apply advanced data protection techniques like column-level masking and row-level security for enhanced data governance and compliance.

Automates guidance for date range analytics, covering SQL, visualization, statistics, and BI, with code generation and validation to support data analytics workflows.