Introduction

Zero-config Data Impact Assessment for dbt Projects

What is PipeRider?

PipeRider is a data impact assessment tool for dbt data projects.

PipeRider compares the data in your dbt project from before and after making data modeling changes and generates Impact Reports and Summaries. Use the generated reports to verify your changes and enable you to merge into prod confidently, without unexpected impact.

What are Impact Reports?

Impact Reports provide details about the impact radius of data modeling changes and downstream impact.

PipeRider surfaces impact in three main places.

Impact Reports

An HTML report that contains a full breakdown of your data including:

  • Impact Summary - An overview of impacted resources and the types of impact.

  • Data profile diff - A detailed comparison of data profile statistics about your data.

  • Lineage Diff - A visualization in the form of a directed acyclic graph (DAG) that shows the impact to the data pipeline after changes.

  • Metrics diff - A graph-based comparison of how dbt metrics have been impacted.

Pull Request Impact Summary

An overview of the data impact in a dbt project that is automatically added to the comments section of a pull request, and includes:

  • Impact Overview - The number and types of impact that have occurred due to code changes in the pull request.

  • Resource Impact - A list of models and an assessment of impact.

  • Metrics Impact - Details of metrics impacted by the code changes.

CLI Impact Summary

A surface-level summary that shows the main areas of impact when running PipeRider on the command line.

Why use PipeRider?

  • See the scope of impact that your dbt project code changes have on your data.

  • Improve your development process by understanding your data and the impact of your changes.

  • Improve your code-review process by verifying data impact before merging code changes.

  • Improve communication between stakeholders and teammates by sharing and discussing Impact Reports.

  • Keep a historical record of data impact reports for future reference.

  • Compare the current state of your project with any point in the past.

Getting started with PipeRider

PipeRider is a zero-config installation for dbt projects, no, really. In the majority of cases you can run PipeRider locally and generate an Impact Report in just two commands.

  1. Follow the Quick Start guide to try out using PipeRider locally.

  2. Sign up for PipeRider Cloud and upload and share your first report.

  3. Set up PipeRider in your CI process using the PipeRider Compare GitHub Action.

Try PipeRider without installing

It’s also possible to try our PipeRider without installing.

Head to Quick Look on PipeRider Cloud and do one of the following:

  • Paste a link to a pull request on your dbt project.

  • Upload two dbt manifest.json files.

PipeRider Cloud will generate an Impact report with schema change and Lineage Diff.

Note that Impact Reports generated from dbt manifest files and GitHub links are more lightweight than the full report and focus on schema change and Lineage Diff.

Join the PipeRider community

NextInstall PipeRider

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