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https://github.com/fivetran/dbt_social_media_reporting

Fivetran's social media reporting dbt package. Combine your Facebook Pages, Instagram Business, Twitter Organic, and LinkedIn Pages social activity using this package.
https://github.com/fivetran/dbt_social_media_reporting

dbt dbt-packages facebook fivetran instagram linkedin social-media twitter

Last synced: 15 days ago
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Fivetran's social media reporting dbt package. Combine your Facebook Pages, Instagram Business, Twitter Organic, and LinkedIn Pages social activity using this package.

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# Social Media Reporting dbt Package ([Docs](https://fivetran.github.io/dbt_social_media_reporting/))



## What does this dbt package do?



This dbt package aggregates and models data from multiple Fivetran social media connectors. The package standardizes the schemas from the various social media connectors and creates a single reporting model for all activity. It enables you to analyze your post performance by clicks, impressions, shares, likes, and comments.



Currently, this package supports the following social media connector types:

  - [Facebook Pages](https://github.com/fivetran/dbt_facebook_pages)

  - [Instagram Business](https://github.com/fivetran/dbt_instagram_business)

  - [LinkedIn Company Pages](https://github.com/fivetran/dbt_linkedin_pages)

  - [Twitter Organic](https://github.com/fivetran/dbt_twitter_organic)

> NOTE: You do _not_ need to have all of these connector types to use this package, though you should have at least two.

- Generates a comprehensive data dictionary of your source and modeled Social Media Reporting data via the [dbt docs site](https://fivetran.github.io/dbt_social_media_reporting/)



This package contains a number of tables, which all build up to the final `social_media_reporting` table. The `social_media_reporting` table combines the data from all of the connectors.



| **Table**    | **Description**                                                                                                        |

| ------------ | ---------------------------------------------------------------------------------------------------------------------- |

| [social_media_reporting__rollup_report](https://github.com/fivetran/dbt_social_media_reporting/blob/main/models/social_media_reporting__rollup_report.sql) | Each record represents a post from a social media account across selected connectors, including post metadata and metrics. |



## How do I use the dbt package?

### Step 1: Pre-Requisites

**Connector**: Have at least one of the below supported Fivetran ad platform connectors syncing data into your warehouse. This package currently supports:

- [Facebook Pages](https://fivetran.com/docs/applications/facebook-pages)

- [Instagram Business](https://fivetran.com/docs/applications/instagram-business)

- [LinkedIn Company Pages](https://fivetran.com/docs/applications/linkedin-company-pages)

- [Twitter Organic](https://fivetran.com/docs/applications/twitter)



> While you need only one of the above connectors to utilize this package, we recommend having at least two to gain the rollup benefit of this package.



- **Database support**: This package has been tested on **BigQuery**, **Snowflake**, **Redshift**, **Postgres** and **Databricks**. Ensure you are using one of these supported databases.



#### Databricks Dispatch Configuration

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.

```yml

dispatch:

  - macro_namespace: dbt_utils

    search_order: ['spark_utils', 'dbt_utils']

```



### Step 2: Installing the Package

Include the following github package version in your `packages.yml`

> Check [dbt Hub](https://hub.getdbt.com/) for the latest installation instructions, or [read the dbt docs](https://docs.getdbt.com/docs/package-management) for more information on installing packages.

```yaml

packages:

  - package: fivetran/social_media_reporting

    version: [">=0.5.0", "<0.6.0"] # we recommend using ranges to capture non-breaking changes automatically

```

Do NOT include the upstream social media packages in this file. The transformation package itself has a dependency on it and will install the upstream packages as well.



Do NOT include the individual social media packages in this file. This package has dependencies on the packages and will install them as well.



### Step 3: Configure Database and Schema Variables

By default, this package looks for your social media reporting data in your target database. If this is not where your app platform data is stored, add the relevant `_database` variables to your `dbt_project.yml` file (see below).



```yml

vars:

    ##Facebook Pages schema and database variables

    facebook_pages_schema: facebook_pages_schema

    facebook_pages_database: facebook_pages_database



    ##Instagram Business schema and database variables

    instagram_business_schema: instagram_business_schema

    instagram_business_database: instagram_business_database



    ##LinkedIn Pages schema and database variables

    linkedin_pages_schema: linkedin_pages_schema

    linkedin_pages_database: linkedin_pages_database



    ##Twitter Organic schema and database variables

    twitter_organic_schema: twitter_organic_schema

    twitter_organic_database: twitter_organic_database

```



#### 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 the Facebook Pages [`dbt_project.yml`](https://github.com/fivetran/dbt_facebook_pages_source/blob/main/dbt_project.yml), Instagram Business [`dbt_project.yml`](https://github.com/fivetran/dbt_instagram_business_source/blob/main/dbt_project.yml), LinkedIn Company Pages [`dbt_project.yml`](https://github.com/fivetran/dbt_linkedin_pages_source/blob/main/dbt_project.yml), and Twitter Organic [`dbt_project.yml`](https://github.com/fivetran/dbt_twitter_organicy_source/blob/main/dbt_project.yml) variable declarations to see the expected names.

    

```yml

vars:

    _identifier: your_table_name 

```



### Step 4: Enabling/Disabling Models

The package assumes that all connector models are enabled, so it will look to pull data from all of the connectors [listed above](https://github.com/fivetran/dbt_social_media_reporting#social-media-reporting). If you don't want to use certain connectors, disable those connectors' models in this package by setting the relevant variables to `false`:



```yml

vars:

    social_media_rollup__twitter_enabled: False

    social_media_rollup__facebook_enabled: False

    social_media_rollup__linkedin_enabled: False

    social_media_rollup__instagram_enabled: False

```



Next, you must disable the models in the unwanted connector's related package, which has its own configuration. Disable the relevant models under the models section of your `dbt_project.yml` file by setting the `enabled` value to `false`.



_Only include the models you want to disable.  Default values are generally `true` but that is not always the case._



```yml

models:

    # disable both instagram business models if not using instagram business

    instagram_business:

        enabled: false

    instagram_business_source:

        enabled: false

  

    # disable both linkedin company pages models if not using linkedin company pages

    linkedin_pages:

        enabled: false

    linkedin_pages_source:

        enabled: false

  

    # disable both twitter organic models if not using twitter organic

    twitter_organic:

        enabled: false

    twitter_organic_source:

        enabled: false

    

    # disable all three facebook pages models if not using facebook pages

    facebook_pages:

        enabled: false

    facebook_pages_source:

        enabled: false

```



### (Optional) Step 5: Additional configurations

#### Unioning Multiple Social Media Connectors

If you have multiple social media connectors in Fivetran, you can use this package on all of them simultaneously. The package will union all of the data together and then pass the unioned table(s) into the reporting model. You will be able to see which source the data came from in the `source_relation` column of each model. To use this functionality, you will need to set either the `union_schemas` or `union_databases` variables:



> IMPORTANT: You _cannot_ use both the `union_schemas` and `union_databases` variables.



```yml

vars:

    ##Schemas variables

    facebook_pages_union_schemas: ['facebook_pages_one','facebook_pages_two']

    linkedin_pages_union_schemas: ['linkedin_company_pages_one', 'linkedin_company_pages_two']

    instagram_business_union_schemas: ['instagram_business_one', 'instagram_business_two', 'instagram_business_three']

    twitter_organic_union_schemas: ['twitter_social_one', 'twitter_social_two', 'twitter_social_three', 'twitter_social_four']



    ##Databases variables

    facebook_pages_union_databases: ['facebook_pages_one','facebook_pages_two']

    linkedin_pages_union_databases: ['linkedin_company_pages_one', 'linkedin_company_pages_two']

    instagram_business_union_databases: ['instagram_business_one', 'instagram_business_two', 'instagram_business_three']

    twitter_organic_union_databases: ['twitter_social_one', 'twitter_social_two', 'twitter_social_three', 'twitter_social_four']

```

For more configuration information, see the individual connector dbt packages ([listed above](https://github.com/fivetran/dbt_social_media_reporting#social-media-reporting)).



## 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](https://hub.getdbt.com/) 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.

```yml

packages:

    - package: fivetran/facebook_pages

      version: [">=0.3.0", "<0.4.0"]



    - package: fivetran/facebook_pages_source

      version: [">=0.3.0", "<0.4.0"]



    - package: fivetran/instagram_business

      version: [">=0.2.0", "<0.3.0"]



    - package: fivetran/instagram_business_source

      version: [">=0.2.0", "<0.3.0"]



    - package: fivetran/twitter_organic

      version: [">=0.3.0", "<0.4.0"]



    - package: fivetran/twitter_organic_source

      version: [">=0.3.0", "<0.4.0"]



    - package: fivetran/linkedin_pages

      version: [">=0.3.0", "<0.4.0"]



    - package: fivetran/linkedin_pages_source

      version: [">=0.3.0", "<0.4.0"]



    - 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?

### 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](https://hub.getdbt.com/fivetran/github/latest/) of the package and refer to the [CHANGELOG](https://github.com/fivetran/dbt_social_media_reporting/blob/main/CHANGELOG.md) and release notes for more information on changes across versions.



### Contributions

These dbt packages are developed by a small team of analytics engineers at Fivetran. However, the packages are made better by community contributions.



We highly encourage and welcome contributions to this package. Check out [this post](https://discourse.getdbt.com/t/contributing-to-a-dbt-package/657) on the best workflow for contributing to a package.



## Are there any resources available?

- If you encounter any questions or want to reach out for help, see the [GitHub Issue](https://github.com/fivetran/dbt_social_media_reporting/issues/new/choose) 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 future dbt package to be developed, then feel free to fill out our [Feedback Form](https://www.surveymonkey.com/r/DQ7K7WW).