What performance optimizations are included?

The skill includes templates for Delta Lake optimization techniques such as Z-Ordering, Liquid Clustering, partition strategies, and automated file compaction.

How does this skill help with data quality?

It provides implementation patterns for quality gates, including schema enforcement, null value checks, and business rule validation to ensure only clean data reaches the Silver and Gold layers.

What is the Medallion Architecture?

It is a data design pattern that organizes data into three layers: Bronze (raw ingested data), Silver (refined and cleansed data), and Gold (curated business-level aggregates).

Does it support real-time data processing?

Yes, the skill includes patterns for incremental processing using Spark Structured Streaming and Delta Lake's streaming capabilities for low-latency updates.

Can I use this for existing Databricks environments?

Absolutely. This skill provides the architectural templates and best practices to standardize existing pipelines or migrate legacy ETL logic to a modern lakehouse structure.

Medallion Architecture for Databricks

Name: Medallion Architecture for Databricks
Author: vivekgana

byvivekgana

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데이터베이스 관리

Implements scalable data lakehouse patterns using Bronze, Silver, and Gold layer design principles and templates.

소개

This skill provides comprehensive guidance and boilerplate for building a robust Medallion (multi-hop) architecture on Databricks. It enables developers to structure data pipelines through raw, refined, and curated layers, incorporating best practices for data quality, schema enforcement, and performance optimization. By providing standardized implementation patterns for both batch and incremental processing, it helps teams migrate from legacy ETL to modern lakehouse architectures while ensuring data integrity, auditability, and high-performance analytics.

주요 기능

Integrated data quality validation frameworks for each pipeline stage
Support for both batch and structured streaming ingestion patterns
2 GitHub stars
Multi-layered design patterns for Bronze, Silver, and Gold data zones
Pre-configured templates for incremental processing and Delta Lake merges
Optimization strategies including Z-Order, Liquid Clustering, and Auto-Optimize

사용 사례

Establishing automated data quality gates and governance across data layers
Migrating traditional data warehouses to a modern Lakehouse architecture
Building scalable production-grade data pipelines on Databricks

소개

주요 기능

Integrated data quality validation frameworks for each pipeline stage
Support for both batch and structured streaming ingestion patterns
2 GitHub stars
Multi-layered design patterns for Bronze, Silver, and Gold data zones
Pre-configured templates for incremental processing and Delta Lake merges
Optimization strategies including Z-Order, Liquid Clustering, and Auto-Optimize

사용 사례

Establishing automated data quality gates and governance across data layers
Migrating traditional data warehouses to a modern Lakehouse architecture
Building scalable production-grade data pipelines on Databricks