Updated August 16, 2023
📣 What does this dbt package do?link
- Materializes Reddit Ads staging tables which leverage data in the format described by this ERD. These staging tables clean, test, and prepare your reddit_ads data from Fivetran's connector for analysis by doing the following:
- Naming the columns for consistency across all packages and for easier analysis
- Adding freshness tests to source data
- Adding column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
- Generates a comprehensive data dictionary of your Reddit Ads data through the dbt docs site.
- These tables are designed to work simultaneously with our Reddit Ads transformation package.
🎯 How do I use the dbt package?link
Step 1: Prerequisiteslink
To use this dbt package, you must have the following:
- At least one Fivetran Reddit Ads connector syncing data into your destination
- A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination
Databricks Dispatch Configurationlink
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.
- macro_namespace: dbt_utils
search_order: ['spark_utils', 'dbt_utils']
Step 2: Install the packagelink
Include the following reddit_ads_source package version in your
- package: fivetran/reddit_ads_source
version: [">=0.2.0", "<0.3.0"]
Step 3: Define database and schema variableslink
By default, this package runs using your destination and the
reddit_ads schema. If this is not where your Reddit Ads data is (for example, if your
reddit_ads schema is named
reddit_ads_fivetran), add the following configuration to your root
(Optional) Step 4: Additional configurationslink
Union multiple connectorslink
If you have multiple reddit_ads connectors in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. The package will union all of the data together and pass the unioned table into the transformations. You will be able to see which source it came from in the
source_relation column of each model. To use this functionality, you will need to set either the
reddit_ads_union_databases variables (cannot do both) in your root
reddit_ads_union_schemas: ['reddit_ads_usa','reddit_ads_canada'] # use this if the data is in different schemas/datasets of the same database/project
reddit_ads_union_databases: ['reddit_ads_usa','reddit_ads_canada'] # use this if the data is in different databases/projects but uses the same schema name
Please be aware that the native
source.yml connection set up in the package will not function when the union schema/database feature is utilized. Although the data will be correctly combined, you will not observe the sources linked to the package models in the Directed Acyclic Graph (DAG). This happens because the package includes only one defined
To connect your multiple schema/database sources to the package models, follow the steps outlined in the Union Data Defined Sources Configuration section of the Fivetran Utils documentation for the union_data macro. This will ensure a proper configuration and correct visualization of connections in the DAG.
Passing Through Additional Metricslink
By default, this package will select
spend from the source reporting tables to store into the staging models. If you would like to pass through additional metrics to the staging models, add the following configurations to your
dbt_project.yml file. These variables allow the pass-through fields to be aliased (
alias) if desired, but not required. Use the following format for declaring the respective pass-through variables:
NOTE Ensure you exercised due diligence when adding metrics to these models. The metrics added by default (clicks, impressions, and cost) have been vetted by the Fivetran team maintaining this package for accuracy. There are metrics included within the source reports, for example, metric averages, which may be inaccurately represented at the grain for reports created in this package. You want to ensure whichever metrics you pass through are indeed appropriate to aggregate at the respective reporting levels provided in this package.
- name: "custom_field_1"
- name: "this_field"
- name: "unique_string_field"
- name: "new_custom_field"
- name: "a_second_field"
Change the build schemalink
By default, this package builds the Reddit Ads staging models within a schema titled (
_reddit_ads_source) in your destination. If this is not where you would like your Reddit Ads staging data to be written to, add the following configuration to your root
+schema: my_new_schema_name # leave blank for just the target_schema
Change the source table referenceslink
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.ymlvariable declarations to see the expected names.
(Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™link
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?link
This dbt package is dependent on the following dbt packages. Please be aware that 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.ymlfile, we highly recommend that you remove them from your root
packages.ymlto avoid package version conflicts.
- package: fivetran/fivetran_utils
version: [">=0.4.0", "<0.5.0"]
- package: dbt-labs/dbt_utils
version: [">=1.0.0", "<2.0.0"]
- package: dbt-labs/spark_utils
version: [">=0.3.0", "<0.4.0"]
🙌 How is this package maintained and can I contribute?link
The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend that 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 to learn how to contribute to a dbt package!
🏪 Are there any resources available?link
- If you have questions or want to reach out for help, please refer to 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.
- Have questions or want to just say hi? Book a time during our office hours on Calendly or email us at firstname.lastname@example.org.