Introduction

PipeRider - Data Reliability Automated.

Code review for data in dbt
PipeRider is an open-source data quality toolkit for data professionals.
PipeRider automatically compares your data to highlight the difference in impacted downstream dbt models so you can merge your Pull Requests with confidence.
How it works:
1.Easy to connect your data source -> PipeRider leverages the connection profiles in your dbt project to connect to the data warehouse
2.Generate profiling statistics of your models to get a high-level overview of your data
3.Compare local changes with the main branch in an HTML report
4.Post a quick summary of the data changes to your PR, so others can be confident too
5.Integrate PipeRider in your CI/CD process through GitHub actions or using PipeRider Cloud
Core concepts
Easy to install: Leveraging dbt's configuration settings, PipeRider can be installed within 2 minutes
Fast comparison: by collecting profiling statistics (e.g. uniqueness, averages, quantiles, histogram) and metric queries, comparing downstream data impact takes little time, speeding up your team's review time
Valuable insights: various profiling statistics displayed in the HTML report give fast insights into your data
Getting Started
Use our Quick Start tutorial and learn how to connect your first data source and get started checking the quality of your data.
Quick Start

Next - Getting Started

Quick Start

Last modified 3mo ago