Skill UI

Automates pivot table creation in data analytics workflows, guiding SQL queries, visualization choices, statistical checks, and BI configurations whenever the user invokes pivot table creator support.

This comprehensive guide provides solutions for common PostHog integration issues, helping developers diagnose and fix tracking failures. It covers critical topics including event capture problems, feature flag misbehavior, API authentication errors (401/429), and user identity fragmentation. Learn best practices for robust data analytics implementation.

This guide provides comprehensive strategies for implementing privacy-safe analytics using PostHog. It addresses critical compliance requirements like GDPR and CCPA, covering explicit consent management (opt-in/opt-out), real-time property sanitization (stripping PII like IP or tokens), and methods for handling Data Subject Access Requests (SAR) and the Right to Erasure. Use this to build highly compliant and privacy-preserving analytics pipelines.

This comprehensive guide outlines the process of migrating analytics data from major platforms like Google Analytics, Mixpanel, Amplitude, or Segment to PostHog. It covers implementing a dual-write strategy, mapping historical event names and properties, and performing bulk historical data imports, ensuring a smooth transition and data continuity.

This comprehensive guide details how to properly set up PostHog for multiple environments (development, staging, production). It emphasizes data isolation by utilizing separate projects, allowing granular control over critical analytics features such as session recording rates, autocapture, and feature flag rollout percentages. This ensures accurate and reliable data tracking across all deployment stages, preventing test data from polluting production analytics.

This guide provides a comprehensive, production-grade architecture for implementing analytics using PostHog. It covers best practices for event taxonomy design, SDK layering (client and server), feature flag management, and integrating the data pipeline (CDP). Ideal for tracking user lifecycle, feature adoption, and revenue in complex web applications.

Provides automated regression analysis guidance, best practices, code snippets, and validation for SQL, BI, visualization, and statistical workflows in data analytics projects.

Automates report template creation within data analytics by guiding SQL, visualization, statistics, and BI best practices, generating ready-to-use configurations and validating outputs.

Automated retention calculator guidance within data analytics workflows, assisting with SQL, visualization, BI, and statistical analysis to produce and validate production-ready outputs for retention insights.

A comprehensive guide to implementing expert customer data tracking across the entire stack. Includes best practices for client-side tracking using Analytics.js (React/Next.js), high-performance server-side tracking via Node.js webhooks, user identity resolution, and data governance strategies for Segment CDP.

Automates SQL query optimization guidance for data analytics workflows, offering best practices, pattern advice, and production-ready code for queries, BI, and visualization tasks whenever the user invokes SQL query optimizer support.

Automates guidance for statistical significance calculations in data analytics, offering triggered best practices, example implementations in SQL, visualization, and BI workflows, plus validation against common standards.