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neo4j-s3-integration

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Load SDTM to Neo4j and S3 with reliability.

Data & Analytics#ETL#regulatory#data-warehouse#neo4j#graph-database#AWS-S3#SDTM
Authorsiddharthchauhan
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill automates loading validated SDTM data into a Neo4j graph database and uploading artifacts to AWS S3, enabling graph-based analytics and persistent storage for regulatory-ready outputs.

Core Features & Use Cases

  • Graph loading: Ingest SDTM domain data as labeled nodes (e.g., SDTM_DM, SDTM_AE) and establish essential domain relationships.
  • Cloud storage integration: Upload SDTM outputs, metadata, and reports to S3 with a consistent key structure.
  • Use Case: Data engineers can deploy this to streamline Phase 7 data warehouse loading by updating both the graph and storage layers in a coordinated workflow.

Quick Start

  1. Configure environment variables for Neo4j (NEO4J_URI, NEO4J_USER, NEO4J_PASSWORD) and AWS (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION).
  2. Install required Python packages, e.g., pip install neo4j boto3.
  3. Run the data-loader for DM and AE domains and verify that nodes are created in Neo4j and files are uploaded to S3.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: neo4j-s3-integration
Download link: https://github.com/siddharthchauhan/ETL/archive/main.zip#neo4j-s3-integration

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