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

• Enables you to understand how users are experiencing and adopting your product. It achieves thi by:

  • Calculating usage of features, pages, guides, and the overall product at the account and individual visitor level
  • Enhancing event stream tables with visitor and product information, referring pages, and features to track the customer journey through the application
  • Creating daily activity timelines for features, pages, and guides that reflect their adoption rates, discoverability, and usage promotion efficacy
  • Directly tying visitors and features together to determine activation rates, power-usage, and churn risk

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.

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

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

If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) dispatch configuration within your dbt_project.yml. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils then the dbt-labs/dbt_utils packages respectively.

dispatch:
  - macro_namespace: dbt_utils
    search_order: ['spark_utils', 'dbt_utils']

Include the following pendo_source 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.yml
packages:
  - package: fivetran/pendo
    version: [">=0.5.0", "<0.6.0"] # we recommend using ranges to capture non-breaking changes automatically

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

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

vars:
  pendo_database: your_database_name
  pendo_schema: your_schema_name 

vars:
  pendo__feature_event_pass_through_columns: # will be passed to pendo__feature_event and stg_pendo__feature_event
    - name:           "custom_crazy_field_name"
      alias:          "normal_field_name"
  pendo__page_event_pass_through_columns: # will be passed to pendo__page_event and stg_pendo__page_event
    - name:           "property_field_id"
      alias:          "new_name_for_this_field_id"
      transform_sql:  "cast(new_name_for_this_field as int64)"
    - name:           "this_other_field"
      transform_sql:  "cast(this_other_field as string)"
  pendo__account_history_pass_through_columns: # will be passed to pendo__account, pendo__feature_event, and pendo__page_event
    - name:           "well_named_field_1"
  pendo__visitor_history_pass_through_columns: # will be passed to pendo__visitor, pendo__feature_event, and pendo__page_event 
    - name:           "well_named_field_2"
  pendo__event_pass_through_columns: # will be passed to stg_pendo__event (in source package only)
    - name:           "well_named_field_3"

...
models:
  pendo:
     schema: my_new_schema_name # leave blank for just the target_schema
    intermediate:
       schema: my_new_schema_name # leave blank for just the target_schema
  pendo_source:
     schema: my_new_schema_name # leave blank for just the target_schema

vars:
  pendo_source:
    pendo_<default_source_table_name>_identifier: your_table_name 

vars:
  pendo_group_identifier: '"Group"' # as an example, must include this quoting pattern and adjust for your exact casing

sources:
  tables:
    - name: group 
      # Add the below
      identifier: GROUP # Or what your group table is named, being mindful of casing
      quoting:
        identifier: true

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

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

    - package: fivetran/pendo_source
      version: [">=0.5.0", "<0.6.0"]

    - package: dbt-labs/spark_utils
      version: [">=0.3.0", "<0.4.0"]

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.

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.

• 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.