kwp-data-sql-queries

Provide SQL syntax and optimization guidance for major data warehouse platforms.

7|5|Updated May 7, 2026
One-click install
npx skills add https://github.com/14790897/MiQi --skill kwp-data-sql-queries
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: kwp-data-sql-queries
Source: https://github.com/14790897/MiQi/tree/main/miqi/skills/kwp/data/sql-queries
Command: npx skills add https://github.com/14790897/MiQi --skill kwp-data-sql-queries

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill resolves the friction of switching between different SQL dialects by providing a unified, expert-level reference for syntax, performance optimization, and complex query patterns across major data platforms.

Core Features & Use Cases

  • Dialect-Specific Syntax: Instant access to syntax for PostgreSQL, Snowflake, BigQuery, Redshift, and Databricks.
  • Advanced Query Patterns: Pre-built templates for window functions, cohort retention, funnel analysis, and deduplication.
  • Performance Optimization: Best practices for indexing, clustering, and query profiling to ensure your analytical workloads remain performant and cost-effective.

Quick Start

Ask the agent to write a SQL query using the Snowflake dialect that calculates a 7-day moving average of revenue using window functions.

Frequently Asked Questions about kwp-data-sql-queries

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a cohort retention SQL query in Snowflake?

To write a cohort retention SQL query in Snowflake, you use pre-built analytical query templates that leverage window functions to group users by initial activity date and track subsequent engagement over time.

What is the best way to optimize BigQuery performance for large analytical workloads?

The best way to optimize BigQuery performance is by applying clustering, indexing best practices, and query profiling to reduce costs. This skill provides specific strategies to keep analytical workloads performant across data warehouses.

Does this SQL syntax guide support PostgreSQL and Redshift dialects?

Yes, this SQL syntax guide supports PostgreSQL and Redshift dialects alongside Snowflake, BigQuery, and Databricks. It provides dialect-specific functions for date arithmetic, string manipulation, and semi-structured data parsing across these environments.

How do I parse semi-structured data using Databricks SQL?

To parse semi-structured data using Databricks SQL, you apply dialect-specific functions designed for navigating and extracting nested JSON fields. This skill offers comprehensive syntax guidance for these data engineering tasks.

Can I get a template for window function calculations like a 7-day moving average?

Yes, you can get templates for window-based calculations like a 7-day moving average. The skill provides pre-built advanced query patterns for window functions, funnel analysis, and deduplication across major data platforms.