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dag-orchestration-patterns

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Master data-pipeline orchestration patterns.

Data & Analytics#orchestration#etl#airflow#data-pipelines#prefect#dagster#dag-patterns
Authorduggal1
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Data engineers need reusable, proven DAG patterns to reliably orchestrate ETL/ELT pipelines across tools like Airflow, Dagster, and Prefect.

Core Features & Use Cases

  • ELT pattern: structure for extracting data, loading raw, and transforming for analytics.
  • Fan-out / Fan-in: parallelize source data processing and merge results for scalable pipelines.
  • Event-pending and MERGE/UPSERT patterns: coordinate data readiness and up-to-date targets with robust retry and idempotency.
  • Partition management and common orchestration strategies for reliable scheduling and monitoring.

Quick Start

Select an orchestration pattern (ELT, fan-out, or event pending) and implement it in your DAG using your preferred toolchain.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: dag-orchestration-patterns
Download link: https://github.com/duggal1/Sapphire-cli/archive/main.zip#dag-orchestration-patterns

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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