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PipeRider

Automates data quality management

For data practitioner who wants to trust their data by:

  • Defining the shape of data, so they can make sure the data will be expected in the future
  • Save time on debugging data,easily discover & discuss any data problems from upstream
  • Socially collaborate across teams on the dataset through data catalog and data insights

Key Features

Instant quality assessment in html

Check single run view

Inject tests to key metrics

Refer to User defined test functions

Compare different test assessments

Check comparison view

Get started

Install PipeRider

$ pip install piperider

By default, PipeRider supports built-in sqlite connector, extra connectors are available:

connectors install
snowflake pip install 'piperider[snowflake]'
postgres pip install 'piperider[postgres]'

Use comma to install multiple connectors in one line:

$ pip install 'piperider[postgres,snowflake]'

Attach piperider to a dbt project

piperider_init

This command creates /.piperider under a dbt project root and generate necessary configurations.

Scan data quality from models

piperider_run

This command scans the models from datasource and create assessment results in /.piperider/output

Generate reports

piperider_report

generate a static html report under current path.

Generate comparison view

piperider_compare

The generated report in html will be placed in the path shown in console

Get involved

[Work In Progress]

Metadata

Release files for piperider-nightly 0.2.0.dev20220614

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