Jira (Source)

This package models Jira data from Fivetran's connector. It uses data in the format described by this ERD. Note: this schema applies to Jira connections set up or fully resynced after September 10, 2020.

This package enriches your Fivetran data by doing the following:

• Adds descriptions to tables and columns that are synced using Fivetran
• Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Models staging tables, which will be used in our transform package

The Jira source dbt package is compatible with BigQuery, Redshift, and Snowflake.

Models

This package contains staging models, designed to work simultaneously with our Jira modeling package. The staging models:

• Remove any rows that are soft-deleted
• Name columns consistently across all packages:
  • Boolean fields are prefixed with is_ or has_
  • Timestamps are appended with _at
  • ID primary keys are prefixed with the name of the table. For example, the issue table's ID column is renamed issue_id.
  • Foreign keys include the table that they refer to. For example, an issue's assignee user ID column is renamed assignee_user_id.

Installation Instructions

Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.

Configuration

By default, this package looks for your Jira data in the jira schema of your target database. If this is not where your Jira data is, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
config-version: 2

vars:
    jira_database: your_database_name
    jira_schema: your_schema_name 

Contributions

Additional contributions to this package are very welcome! Please create issues or open PRs against master. Check out this post on the best workflow for contributing to a package.

Resources:

• Provide feedback on our existing dbt packages or what you'd like to see next
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• Learn how to orchestrate dbt transformations with Fivetran here.
• Learn more about Fivetran overall in our docs
• Check out Fivetran's blog
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