Great Expectations: Automated Data Profiling on AWS

About Great Expectations Stack

The Great Expectations Stack AMI delivers a fully configured data quality and validation environment, ideal for data engineers, analysts, and pipeline developers. Pre-installed with Great Expectations and Jupyter Notebook, this AMI is optimized for AWS, allowing you to deploy a data testing and documentation workflow within minutes—no manual configuration or setup needed.

Whether you’re validating incoming datasets, building data quality checks, or generating automated documentation, this AMI provides a solid foundation for trustworthy data pipelines. With Jupyter Notebook accessible via the browser, you gain an intuitive interface for creating, testing, and managing expectations interactively—all from a secure and scalable EC2 environment. Designed to support modern data workflows, the Great Expectations Stack AMI helps you maintain high data quality from ingestion to analytics.

Key Features of Great Expectations Stack

• One-Click Deployment: Instantly launch a fully functional data validation environment with Great Expectations and Jupyter Notebook on AWS EC2
• Pre-Configured for Data Quality: Includes Great Expectations, Jupyter, and essential Python libraries—ready to use without manual setup
• Web-Based Notebook Access: Create, run, and visualize your data tests and documentation directly from a browser-based Jupyter interface
• Optimized for AWS: Designed for high performance on a wide range of EC2 instance types to fit small-scale and enterprise data needs
• Interactive Data Profiling: Generate detailed data summaries and expectation suites to catch anomalies early in your pipeline
• Automated Data Documentation: Automatically create human-readable documentation from your expectation suites
• Customizable Validation Workflows: Tailor validation rules and batch processing to match your data sources and business logic
• Secure and Self-Hosted: Maintain full control over data privacy and access by running in your isolated AWS EC2 environment

Included With Application

Fully integrated data validation and profiling environment with browser-based Jupyter Notebook access, pre-installed Great Expectations, and essential Python libraries—ideal for building, testing, and documenting reliable data pipelines.