Skill UI

Automates Google BigQuery workflows via Rube MCP and Metabase, letting you run native SQL/MBQL queries, fetch metadata, and explore schemas before querying.

This skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.

An advanced workflow orchestrator designed to perform multi-phase, deep-dive schema optimization on large datasets (e.g., BigQuery exports). It systematically analyzes schema structure, identifies unused or redundant fields, assesses potential impact, and generates a comprehensive, actionable report with recommended optimization strategies and estimated savings.

Vaex is a high-performance Python library for lazy out-of-core DataFrames that process billions of rows without RAM. Use it to analyze massive CSV/HDF5/Arrow/Parquet tables, compute fast statistics, visualize big data, and build scikit-learn pipelines.

Gtars is a high-performance toolkit written in Rust with Python bindings, specialized for computational genomics. It provides advanced functionality for manipulating genomic interval data, including overlap detection (IGD), coverage track generation (BigWig), and genomic tokenization for machine learning preprocessing. Ideal for researchers working with BED files, single-cell data, and ML-driven biological models.

Vaex is a high-performance Python library for lazy out-of-core DataFrames that process billions of rows without RAM. Use it to analyze massive CSV/HDF5/Arrow/Parquet tables, compute fast statistics, visualize big data, and build scikit-learn pipelines.

Builds a robust, automated workflow to export critical sales data—including forecasts, quota details, adjustments, and CRM totals—from Clari CRM to a designated data warehouse. The pipeline supports multiple targets like Snowflake, BigQuery, and PostgreSQL, ensuring that real-time revenue intelligence is available for advanced analytics and business reporting.

A comprehensive guide to setting up and securing API access for Clari. Learn how to generate API tokens, configure environment variables, and test connectivity to export critical revenue intelligence and forecast data to data warehouses like Snowflake or BigQuery. Includes steps for both standard Clari API and Copilot API integration.

This expert acts as a dedicated data analysis partner for Product Managers. It helps users explore data, write complex queries (e.g., SQL, BigQuery), analyze key metrics, and create structured dashboards. Use this tool when you need to derive actionable insights from complex datasets, compare user cohorts, or understand product performance trends to inform critical business decisions.

A comprehensive guide detailing the process of migrating data warehouses to Snowflake from major sources like Amazon Redshift, Google BigQuery, or on-premise databases. This resource covers critical steps including schema conversion (handling dialect differences like STRUCT/ARRAY to VARIANT), robust data transfer methods (S3/Cloud Storage, Python/Pandas), data validation techniques (checksums, row counts), and essential SQL syntax translation patterns.