Asana dbt Package (Docs)

What does this dbt package do?

• Produces modeled tables that leverage Asana data from Fivetran's connector in the format described by this ERD and builds off of the output of our Asana source package.

• Enhances the task, users, projects, teams, and tags tables. Each of these tables is enriched with metrics that reflect the volume and breadth of current work and also the velocity of completed work.

• Provides a daily metrics table, which lays out a timeline of task creations and completions to show the overall pace of deliverables.

• Generates a comprehensive data dictionary of your source and modeled Asana data through the dbt docs site.

• These tables are designed to work simultaneously with our Asana source package.

The following table provides a detailed list of all tables materialized within this package by default.

TIP: See more details about these tables in the package's dbt docs site.

Table	Description
asana__task	Each record represents an Asana task, enriched with data about its assignee, projects, sections, tasks, teams, tags, parent task, comments, followers, and activity.
asana__user	Each record represents an Asana user, enriched with metrics about their completed tasks, open tasks, and the projects they work on. Also includes data about the user's most recently completed task and their next due task.
asana_project	Each record represents an Asana project, enriched with metrics about their completed tasks, open tasks, and the users involved in the project. Also includes data about the project's most recently completed task and next due tasks.
asana__team	Each record represents an Asana team, enriched with data about their completed tasks, open tasks, their projects, and the users involved with the team.
asana__tag	Each record represents an Asana tag, enriched with metrics about open and completed tasks associated with the tag.
asana__daily_metrics	Each record represents a single day, enriched with metrics about tasks opened at created that day.

How do I use the dbt package?

Step 1: Prerequisites

To use this dbt package, you must have the following:

• At least one Fivetran Asana connector syncing data into your destination.
• A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

Step 2: Install the package

Include the following asana package version in your packages.yml file.

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

packages:
  - package: fivetran/asana
    version: [">=0.8.0", "<0.9.0"] # we recommend using ranges to capture non-breaking changes automatically

Do NOT include the asana_source package in this file. The transformation package itself has a dependency on it and will install the source package as well.

Step 3: Define database and schema variables

By default, this package runs using your destination and the asana schema. If this is not where your Asana data is (for example, if your Asana schema is named asana_fivetran), add the following configuration to your root dbt_project.yml file:

config-version: 2

vars:
  asana_source:
    asana_database: your_database_name
    asana_schema: your_schema_name 

(Optional) Step 4: Additional configurations

Expand for configurations

Passing Through Additional Columns

This package allows users to include additional columns to the source task table. To do this, include any additional columns to the asana_source pass-through variables to ensure the downstream columns are present.

vars:
  asana_source:
    task_pass_through_columns: [custom_status, custom_department]

Changing the Build Schema

By default this package will build the Asana staging models within a schema titled (<target_schema> + _stg_asana) and the Asana final models with a schema titled (<target_schema> + _asana) in your target database. If this is not where you would like your modeled Asana data to be written to, add the following configuration to your root dbt_project.yml file:

models:
  asana:
    +schema: my_new_schema_name # leave blank for just the target_schema
  asana_source:
    +schema: my_new_schema_name # leave blank for just the target_schema

Change the source table references

If an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:

IMPORTANT: See this project's dbt_project.yml variable declarations to see the expected names.

vars:
    asana_<default_source_table_name>_identifier: your_table_name 

(Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™

Expand for more details

Fivetran offers the ability for you to orchestrate your dbt project through Fivetran Transformations for dbt Core™. Learn how to set up your project for orchestration through Fivetran in our Transformations for dbt Core setup guides.

Does this package have dependencies?

This dbt package is dependent on the following dbt packages. These dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.

IMPORTANT: If you have any of these dependent packages in your own packages.yml file, we highly recommend that you remove them from your root packages.yml to avoid package version conflicts.

packages:
    - package: fivetran/asana_source
      version: [">=0.8.0", "<0.9.0"]

    - package: fivetran/fivetran_utils
      version: [">=0.4.0", "<0.5.0"]

    - package: dbt-labs/dbt_utils
      version: [">=1.0.0", "<2.0.0"]

How is this package maintained and can I contribute?

Package Maintenance

The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.

Contributions

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.

We highly encourage and welcome contributions to this package. Check out this dbt Discourse article on the best workflow for contributing to a package.

Are there any resources available?

• If you have questions or want to reach out for help, see the GitHub Issue section to find the right avenue of support for you.
• If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our Feedback Form.