Skill UI

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

Guides data engineering patterns for ETL pipelines, Spark analytics, and quality checks, showcasing Python and SQL snippets to extract, transform, load, validate, and model sales data in modern warehouses.

This skill provides comprehensive guidelines for detecting Business Email Compromise (BEC), a sophisticated fraud scheme. It covers detection techniques using email gateway rules, behavioral analytics, and robust financial process controls. Learn to identify red flags like unusual payment requests, domain mismatches, and patterns of social engineering to protect against financial loss.

A comprehensive guide for authors targeting the IEEE International Conference on Data Engineering (ICDE). This skill helps assess venue fit, re-frame manuscripts from journal/arXiv styles, and structure papers for top CS conferences. It details required evidence (system architecture, realistic workloads) and best practices for positioning contributions in data engineering, database systems, and analytics.

A workflow for building features guided by data insights, A/B testing, and continuous measurement, covering exploratory data analysis, hypothesis formation, experiment design, analytics instrumentation, and implementation.

Master ClickHouse database patterns for high-performance OLAP workloads. Learn table design strategies like MergeTree, query optimization techniques, efficient data insertion methods, and materialized views for real-time analytics. Includes best practices for SQL aggregation and performance monitoring.