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Open Source Data Observability Quickstart Demo

Data breaks. Servers break. Your toolchain breaks. Ensure your team is the first to know and the first to solve with visibility across and down your data estate. Save time with simple, fast data quality test generation and execution. Trust your data, tools, and systems end-to-end. DataKitchen's Open Source Data Observability comprises two closely related products: DataOps Observability and DataOps Data Quality TestGen.

Two products overview

Watch Demonstration

Install TestGen

Install on Mac / Linux

Recommended Docker install

Install on Windows

Recommended Docker install

Install via pip

Python package install

Install Observability

Install on Mac / Linux

Recommended Docker install

Install on Windows

Recommended Docker install

Key features and benefits

Find data quality issues in new data. TestGen profiles your data and automatically generates tests to catch anomalies before they reach downstream systems.

Find data quality issues

Watch for data quality anomalies. Continuous monitoring alerts you to problems as they happen — freshness gaps, volume changes, schema drift, and metric anomalies.

Watch for anomalies

Monitor multi-tool, multi-data production processes. Observability tracks data journeys across your entire toolchain, giving you end-to-end visibility.

Monitor production processes

Make fast, safe development changes. With quality guardrails in place, your team can iterate quickly and deploy with confidence.

Fast, safe changes

Set up demo data

After installing both products using the install links above, seed them with demo data for the quickstart tutorial:

# Set up TestGen demo data
python3 dk-installer.py tg run-demo

# Set up Observability demo data
python3 dk-installer.py obs run-demo

# Start the Observability Agent Heartbeat demo
python3 dk-installer.py obs run-heartbeat-demo

Then follow the quick start guide below to explore the product features and capabilities. It should take less than one hour to complete.

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