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* MagicBot/documentation-updates

* Update README.md

* Update README.md

model to table updates

---------

Co-authored-by: Avinash Kunnath <[email protected]>
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23 changes: 21 additions & 2 deletions .github/ISSUE_TEMPLATE/bug-report.yml
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@@ -1,7 +1,7 @@
name: 🐞 Bug
description: Report a bug or an issue you've found within the dbt package
title: "[Bug] <title>"
labels: ["bug", "triage"]
labels: ["type:bug"]
body:
- type: markdown
attributes:
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description: A concise description of what you expected to happen.
validations:
required: true
- type: textarea
attributes:
label: Possible solution
description: Were you able to investigate and/or discover a potential fix to this bug in your investigation? If so, it would be much appreciated if you could submit code samples to show us how your fix resolved this issue.
validations:
required: false
- type: textarea
attributes:
label: dbt Project configurations
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- other (mention it in "Additional Context")
validations:
required: true
- type: dropdown
id: orchestration_type
attributes:
label: How are you running this dbt package?
multiple: true
options:
- Fivetran Quickstart Data Model
- Fivetran Transformations
- dbt Core™
- dbt Cloud™
- other (mention it in "Additional Context")
validations:
required: true
- type: textarea
attributes:
label: dbt Version
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description: Our team will assess this issue and let you know if we will add it to a future sprint. However, if you would like to expedite the solution, we encourage you to contribute to the package via a PR. Our team will then work with you to approve and merge your contributions as soon as possible.
options:
- label: Yes.
- label: Yes, but I will need assistance and will schedule time during our [office hours](https://calendly.com/fivetran-solutions-team/fivetran-solutions-team-office-hours) for guidance
- label: Yes, but I will need assistance.
- label: No.
required: false
11 changes: 9 additions & 2 deletions .github/ISSUE_TEMPLATE/feature-request.yml
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name: 🎉 Feature
description: Suggest a new feature for the Fivetran dbt package
title: "[Feature] <title>"
labels: ["enhancement"]
labels: ["type:enhancement"]
body:
- type: markdown
attributes:
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description: A clear and concise description of what you want to happen and why you want the new feature.
validations:
required: true
- type: textarea
attributes:
label: How would you implement this feature?
description: |
How would you build out this feature with your existing data? Any code examples you can provide to help accelerate development on this issue?
validations:
required: true
- type: textarea
attributes:
label: Describe alternatives you've considered
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description: Our team will assess this feature and let you know if we will add it to a future sprint. However, if you would like to expedite the feature, we encourage you to contribute to the package via a PR. Our team will then work with you to approve and merge your contributions as soon as possible.
options:
- label: Yes.
- label: Yes, but I will need assistance and will schedule time during your [office hours](https://calendly.com/fivetran-solutions-team/fivetran-solutions-team-office-hours) for guidance.
- label: Yes, but I will need assistance.
- label: No.
required: false
- type: textarea
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8 changes: 7 additions & 1 deletion .github/pull_request_template.md
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<!--- To select a checkbox you simply need to add an "x" with no spaces between the brackets (eg. [x] Yes). -->
- [ ] Yes

**Provide an emoji that best describes your current mood**
**Typically there are additional maintenance changes required before this will be ready for an upcoming release. Are you comfortable with the Fivetran team making a few commits directly to your branch?**
<!--- If you select Yes this will help expedite your PR in case there are small changes required before approval. We encourage you not to use this branch in a production environment as we may make additional updates. -->
<!--- If you select No, we will not make any changes directly to your branch and will either communicate any planned changes via the PR thread or will merge your PR into a separate branch so we may make changes without modifying your branch.. -->
- [ ] Yes
- [ ] No

**If you had to summarize this PR in an emoji, which would it be?**
<!--- For a complete list of markdown compatible emojis check our this git repo (https://gist.github.com/rxaviers/7360908) -->
:dancer:

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10 changes: 10 additions & 0 deletions .quickstart/quickstart.yml
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Expand Up @@ -14,3 +14,13 @@ destination_configurations:
dispatch:
- macro_namespace: dbt_utils
search_order: [ 'spark_utils', 'dbt_utils' ]

public_models: [
"fivetran_platform__schema_changelog",
"fivetran_platform__connector_daily_events",
"fivetran_platform__audit_user_activity",
"fivetran_platform__connector_status",
"fivetran_platform__usage_mar_destination_history",
"fivetran_platform__audit_table",
"fivetran_platform__mar_table_history"
]
59 changes: 29 additions & 30 deletions README.md
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</p>

# Fivetran Platform dbt Package ([Docs](https://fivetran.github.io/dbt_fivetran_log/))
# 📣 What does this dbt package do?
## What does this dbt package do?
- Generates a comprehensive data dictionary of your Fivetran Platform connector (previously called Fivetran Log) data via the [dbt docs site](https://fivetran.github.io/dbt_fivetran_log/)

- Produces staging models in the format described by [this ERD](https://fivetran.com/docs/logs/fivetran-platform#schemainformation) which clean, test, and prepare your Fivetran data from our free [Fivetran Platform connector](https://fivetran.com/docs/logs/fivetran-platform) and generates analysis ready end models.
Expand All @@ -26,44 +26,44 @@
- Keeping an audit log of user-triggered actions across your Fivetran instance

<!--section="fivetran_platform_transformation_model"-->
Refer to the table below for a detailed view of all models materialized by default within this package. Additionally, check out our [docs site](https://fivetran.github.io/dbt_fivetran_log/#!/overview/fivetran_platform?g_v=1&g_e=seeds) for more details about these models.
## Models
Refer to the table below for a detailed view of all tables materialized by default within this package. Additionally, check out our [docs site](https://fivetran.github.io/dbt_fivetran_log/#!/overview/fivetran_platform?g_v=1&g_e=seeds) for more details about these tables.
### Tables

| **model** | **description** |
| **Table** | **Description** |
| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [fivetran_platform__connector_status](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__connector_status) | Each record represents a connector loading data into a destination, enriched with data about the connector's data sync status. |
| [fivetran_platform__mar_table_history](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__mar_table_history) | Each record represents a table's free, paid, and total volume for a month, complete with data about its connector and destination. |
| [fivetran_platform__usage_mar_destination_history](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__usage_mar_destination_history) | Table of each destination's usage and active volume, per month. Includes the usage per million MAR and MAR per usage. Usage either refers to a dollar or credit amount, depending on customer's pricing model. Read more about the relationship between usage and MAR [here](https://www.fivetran.com/legal/service-consumption-table). |
| [fivetran_platform__connector_daily_events](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__connector_daily_events) | Each record represents a daily measurement of the API calls, schema changes, and record modifications made by a connector, starting from the date on which the connector was set up. |
| [fivetran_platform__schema_changelog](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__schema_changelog) | Each record represents a schema change (altering/creating tables, creating schemas, and changing schema configurations) made to a connector and contains detailed information about the schema change event. |
| [fivetran_platform__audit_table](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__audit_table) | Replaces the deprecated [`_fivetran_audit` table](https://fivetran.com/docs/getting-started/system-columns-and-tables#audittables). Each record represents a table being written to during a connector sync. Contains timestamps related to the connector and table-level sync progress and the sum of records inserted/replaced, updated, and deleted in the table. |
| [fivetran_platform__audit_user_activity](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__audit_user_activity) | Each record represents a user-triggered action in your Fivetran instance. This model is intended for audit-trail purposes, as it can be very helpful when trying to trace a user action to a [log event](https://fivetran.com/docs/logs#logeventlist) such as a schema change, sync frequency update, manual update, broken connection, etc. |
| [fivetran_platform__audit_user_activity](https://fivetran.github.io/dbt_fivetran_log/#!/model/model.fivetran_log.fivetran_platform__audit_user_activity) | Each record represents a user-triggered action in your Fivetran instance. This table is intended for audit-trail purposes, as it can be very helpful when trying to trace a user action to a [log event](https://fivetran.com/docs/logs#logeventlist) such as a schema change, sync frequency update, manual update, broken connection, etc. |
<!--section-end-->

# 🎯 How do I use the dbt package?
## Step 1: Pre-Requisites
- **Connector**: Have the Fivetran Platform connector syncing data into your warehouse.
## How do I use the dbt package?
### Step 1: Pre-Requisites
- **Connector**: Have the Fivetran Platform connector syncing data into your warehouse.
- **Database support**: This package has been tested on **BigQuery**, **Snowflake**, **Redshift**, **Postgres**, **Databricks**, and **SQL Server**. Ensure you are using one of these supported databases.

### Databricks Dispatch Configuration
#### 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']
```
### Database Incremental Strategies
#### Database Incremental Strategies
For models in this package that are materialized incrementally, they are configured to work with the different strategies available to each supported warehouse.
For **BigQuery** and **Databricks All Purpose Cluster runtime** destinations, we have chosen `insert_overwrite` as the default strategy, which benefits from the partitioning capability.
For **BigQuery** and **Databricks All Purpose Cluster runtime** destinations, we have chosen `insert_overwrite` as the default strategy, which benefits from the partitioning capability.
> For Databricks SQL Warehouse destinations, models are materialized as tables without support for incremental runs.

For **Snowflake**, **Redshift**, and **Postgres** databases, we have chosen `delete+insert` as the default strategy.
For **Snowflake**, **Redshift**, and **Postgres** databases, we have chosen `delete+insert` as the default strategy.

> Regardless of strategy, we recommend that users periodically run a `--full-refresh` to ensure a high level of data quality.

## Step 2: Installing the Package
### Step 2: Installing the Package
Include the following Fivetran Platform package version range 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
Expand All @@ -74,7 +74,7 @@ packages:

> Note that although the source connector is now "Fivetran Platform", the package retains the old name of "fivetran_log".

## Step 3: Define Database and Schema Variables
### Step 3: Define Database and Schema Variables
By default, this package will run using your target database and the `fivetran_log` schema. If this is not where your Fivetran Platform data is (perhaps your fivetran platform schema is `fivetran_platform`), add the following configuration to your root `dbt_project.yml` file:

```yml
Expand All @@ -83,7 +83,7 @@ vars:
fivetran_platform_schema: your_schema_name # default is fivetran_log
```

## Step 4: Disable Models for Non Existent Sources
### Step 4: Disable Models for Non Existent Sources
If you do not leverage Fivetran RBAC, then you will not have the `user` or `destination_membership` sources. It's also possible you might not have any To disable the corresponding functionality in the package, you must add the following variable(s) to your root `dbt_project.yml` file. By default, all variables are assumed to be `true`:

```yml
Expand All @@ -92,9 +92,9 @@ vars:
fivetran_platform_using_user: false # this will disable only the user logic
```

## (Optional) Step 5: Additional Configurations
### (Optional) Step 5: Additional Configurations

### Change the Build Schema
#### Change the Build Schema
By default this package will build the Fivetran staging models within a schema titled (<target_schema> + `_stg_fivetran_platform`) and the Fivetran Platform final models within your <target_schema> + `_fivetran_platform` in your target database. If this is not where you would like you Fivetran staging and final models to be written to, add the following configuration to your root `dbt_project.yml` file:

```yml
Expand All @@ -105,22 +105,22 @@ models:
+schema: my_new_staging_models_schema # leave blank for just the target_schema
```

### Change the Source Table References
#### Change the Source Table References
If an individual source table has a different name than expected (see this projects [dbt_project.yml](https://github.com/fivetran/dbt_fivetran_log/blob/main/dbt_project.yml) variable declarations for expected names), provide the name of the table as it appears in your warehouse to the respective variable as identified below:
```yml
vars:
fivetran_platform_<default_table_name>_identifier: your_table_name
```

## (Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™
### (Optional) Step 6: Orchestrate your models with Fivetran Transformations for dbt Core™
<details><summary>Expand for details</summary>
<br>

Fivetran offers the ability for you to orchestrate your dbt project through [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt). Refer to the linked docs for more information on how to setup your project for orchestration through Fivetran.
Fivetran offers the ability for you to orchestrate your dbt project through [Fivetran Transformations for dbt Core™](https://fivetran.com/docs/transformations/dbt). Refer to the linked docs for more information on how to setup your project for orchestration through Fivetran.
</details>

# 🔍 Does this package have dependencies?
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 below packages, refer to the [dbt hub](https://hub.getdbt.com/) site.
## 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 below packages, refer to the [dbt hub](https://hub.getdbt.com/) site.
> **If you have any of these dependent packages in your own `packages.yml` I highly recommend you remove them to ensure there are no package version conflicts.**
```yml
packages:
Expand All @@ -137,16 +137,15 @@ packages:
version: [">=0.9.0", "<1.0.0"]
```

# 🙌 How is this package maintained and can I contribute?
## Package Maintenance
## 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/fivetran_log/latest/) of the package and refer to the [CHANGELOG](https://github.com/fivetran/dbt_fivetran_log/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!
### 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!
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, please refer to the [GitHub Issue](https://github.com/fivetran/dbt_fivetran_log/issues/new/choose) section to find the right avenue of support for you.
## 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_fivetran_log/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).
- Have questions or want to be part of the community discourse? Create a post in the [Fivetran community](https://community.fivetran.com/t5/user-group-for-dbt/gh-p/dbt-user-group) and our team along with the community can join in on the discussion!

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