bugfix/sla-investigations

.quickstart/quickstart.yml

@@ -8,7 +8,6 @@ table_variables:
     - daylight_time
     - schedule_holiday
     - schedule
-    - ticket_schedule
     - time_zone
   using_domain_names:
     - domain_name

CHANGELOG.md

@@ -1,3 +1,22 @@
+# dbt_zendesk v0.14.0
+
+[PR #136](https://github.com/fivetran/dbt_zendesk/pull/136) includes the following changes:
+
+## Bug Fixes
+- Converted the `zendesk__sla_policies` metric for `sla_elapsed_time` to be reported in minutes to the second as opposed to just the nearest rounded minute. This ensures more accurate reporting.
+- Updated the `int_zendesk__reply_time_combined` model to additionally account for the following business hour scenarios as they were erroneously being filtered out in previous versions of the package:
+   - A ticket is first replied to outside SLA schedules
+   - A ticket is has not yet received an agent reply
+- Included additional logic within the `int_zendesk__ticket_schedules` model to more accurately select the **active** default schedule.
+  - Previously the model could possibly select a deleted schedule. This update ensures only an active schedule is selected.
+- Overhauled the logic used to calculate `sla_breach_at` within the `zendesk__sla_policies` and upstream models for reply time SLAs. It was found this field was inconsistent with the actual breach/achieve time of an SLA. The overhaul should now ensure reply time SLA is accurate to either be the time of the SLA breach or achieve event.
+- Adjusted the `next_reply_time` SLA elapsed time metric calculation to also take into consideration the ticket solved event as a valid SLA event. Previously if a reply time SLA was attached to a ticket and there was no reply, but the ticket was closed then the SLA would be breached. This update ensures a closed event serves as a route for the SLA to be achieved or breached.
+- Modified the logic that matches schedule weeks when calculating reply time business metrics. Previously long running SLAs would be excluded from the final model, now all reply time business SLAs regardless of sla elapsed duration will be included in the end `zendesk__sla_policies` model.
+
+## Documentation Updates
+- Updated "Zendesk" references within the README to now refer to "Zendesk Support" in order to more accurately reflect the name of the Fivetran Zendesk Support Connector.
+- Added new entries to the DECISIONLOG to highlight nuances and opinionated stances this package uses when calculating business metrics and `first_reply_time` SLAs.
+
 # dbt_zendesk v0.13.1
 
 [PR #128](https://github.com/fivetran/dbt_zendesk/pull/128) includes the following changes:

DECISIONLOG.md

@@ -1,8 +1,19 @@
 # Decision Log
 
+## No Historical Schedule Reference
+At the current moment the Fivetran Zendesk Support connector does not contain historical data of schedules. This means if a schedule is created in the Zendesk UI and remains untouched for years, but then is adjusted in the current month you will see the data synced in the raw `schedule` table to reflect the current adjusted schedule. As a result the raw data will lose all historical reference of what this schedule range was previously.
+
+Therefore, if you are leveraging the `using_schedule` variable as `true` to replicate business hour metrics this data model will only have a reference to the current range of any given schedule. This means tickets from the previous two years that were leveraging the __old__ schedule will not be reported as using the __new__ schedule. If this data limitation is a concern to you, we recommend opening a [Fivetran Support Feature Request](https://support.fivetran.com/hc/en-us/community/topics/360001909373-Feature-Requests?sort_by=votes) to enhance the Zendesk Support connector to include historical schedule data.
+
+## Zendesk First Reply Time SLA Opinionated Logic
+The logic for `first_reply_time` breach/achievement metrics within the `zendesk__ticket_metrics` and `zendesk__sla_policies` models are structured on the Zendesk definition of [first reply time SLA events](https://support.zendesk.com/hc/en-us/articles/4408821871642-Understanding-ticket-reply-time?page=2#topic_jvw_nqd_1hb). For example, this data model calculates first reply time to be the duration of time (business or calendar) between the creation of the ticket and the first public comment from either an `agent` or `admin`. This holds true regardless of when the first reply time SLA was applied to the ticket.
+
+This means if a ticket has been opened for a number of days and then a `first_reply_time` SLA is applied to the ticket, this data model will still calculate the `first_reply_time` metric as the duration of time from the creation of the ticket and the first public comment, **not** from when the SLA was applied. 
+
+We have found that some reports of `sla_breach_at`, `sla_elapsed_time`, and the `first_reply_time_*` metrics in the aforementioned models do not match the metrics provided in the Zendesk UI. This is due to certain reports in Zendesk calculating the `first_reply_time` as the first public `agent` or `admin` reply following the SLA being applied to the ticket. We are taking the stance in this data model that this is not reflective of the `first_reply_time` metric and will continue to report the `first_reply_time` as mentioned above. As a result, some of your `first_reply_time` metrics may potentially not match exactly what you see reported in the Zendesk UI reports.
 
 ## Zendesk Backlog Tickets
-- You may find some discrepancies between what Zendesk reports and our model the total number of backlog tickets on a given day. After investigating this we have realized this is due to Zendesk taking a snapshot of each day sometime in the 23rd hour as stated in their [article.](https://support.zendesk.com/hc/en-us/articles/4408819342490-Why-does-the-Backlog-dataset-only-show-the-Backlog-recorded-Hour-as-23-).
+- You may find some discrepancies between what Zendesk reports and our model the total number of backlog tickets on a given day. After investigating this we have realized this is due to Zendesk taking a snapshot of each day sometime in the 23rd hour as stated in their [article](https://support.zendesk.com/hc/en-us/articles/4408819342490-Why-does-the-Backlog-dataset-only-show-the-Backlog-recorded-Hour-as-23-).
 
 ```
 Because backlog data is captured on a per-day basis, it cannot be segmented hourly. The Backlog recorded - Hour is listed as 23 because data is captured daily between 11 pm, 12 am, or 1 am depending on factors like Daylight Saving Time (DST). 

README.md

@@ -13,25 +13,27 @@
         <img src="https://img.shields.io/badge/Fivetran_Quickstart_Compatible%3F-yes-green.svg" /></a>
 </p>
 
-# Zendesk Modeling dbt Package ([Docs](https://fivetran.github.io/dbt_zendesk/))
+# Zendesk Support Modeling dbt Package ([Docs](https://fivetran.github.io/dbt_zendesk/))
 # 📣 What does this dbt package do?
-- Produces modeled tables that leverage Zendesk data from [Fivetran's connector](https://fivetran.com/docs/applications/zendesk) in the format described by [this ERD](https://fivetran.com/docs/applications/zendesk#schemainformation) and build off the output of our [zendesk source package](https://github.com/fivetran/dbt_zendesk_source).
+- Produces modeled tables that leverage Zendesk Support data from [Fivetran's connector](https://fivetran.com/docs/applications/zendesk) in the format described by [this ERD](https://fivetran.com/docs/applications/zendesk#schemainformation) and build off the output of our [zendesk source package](https://github.com/fivetran/dbt_zendesk_source).
 - Enables you to better understand the performance of your Support team. It calculates metrics focused on response times, resolution times, and work times for you to analyze. It performs the following actions:
   - Creates an enriched ticket model with relevant resolution, response time, and other metrics
   - Produces a historical ticket field history model to see velocity of your tickets over time
-  - Converts metrics to business hours for Zendesk Professional or Enterprise users
-  - Calculates SLA policy breaches for Zendesk Professional or Enterprise users
-- Generates a comprehensive data dictionary of your source and modeled Zendesk data through the [dbt docs site](https://fivetran.github.io/dbt_zendesk/).
+  - Converts metrics to business hours for Zendesk Support Professional or Enterprise users
+  - Calculates SLA policy breaches for Zendesk Support Professional or Enterprise users
+- Generates a comprehensive data dictionary of your source and modeled Zendesk Support data through the [dbt docs site](https://fivetran.github.io/dbt_zendesk/).
+
+> Note: Tickets from the Zendesk Support Chat channel will not populate in this package as the Fivetran connector does not currently support Chat based tickets. This is a feature request that has been flagged. 
 
 <!--section="zendesk_transformation_model"-->
 The following table provides a detailed list of final models materialized within this package by default. 
 > TIP: See more details about these models in the package's [dbt docs site](https://fivetran.github.io/dbt_zendesk/#!/overview?g_v=1).
 
 | **model**                    | **description**                                                                                                                                                 |
 | ---------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| [zendesk__ticket_metrics](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_metrics)       | Each record represents a Zendesk ticket, enriched with metrics about reply times, resolution times, and work times.  Calendar and business hours are supported.  |
-| [zendesk__ticket_enriched](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_enriched)      | Each record represents a Zendesk ticket, enriched with data about its tags, assignees, requester, submitter, organization, and group.                           |
-| [zendesk__ticket_summary](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_summary)           | A single record table containing Zendesk ticket and user summary metrics.                                                              |
+| [zendesk__ticket_metrics](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_metrics)       | Each record represents a Zendesk Support ticket, enriched with metrics about reply times, resolution times, and work times.  Calendar and business hours are supported.  |
+| [zendesk__ticket_enriched](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_enriched)      | Each record represents a Zendesk Support ticket, enriched with data about its tags, assignees, requester, submitter, organization, and group.                           |
+| [zendesk__ticket_summary](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_summary)           | A single record table containing Zendesk Support ticket and user summary metrics.                                                              |
 | [zendesk__ticket_backlog](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_backlog)           | A daily historical view of the ticket field values defined in the `ticket_field_history_columns` variable for all backlog tickets. Backlog tickets being defined as any ticket not in a 'closed', 'deleted', or 'solved' status.                                                             |
 | [zendesk__ticket_field_history](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__ticket_field_history) | A daily historical view of the ticket field values defined in the `ticket_field_history_columns` variable and the corresponding updater fields defined in the `ticket_field_history_updater_columns` variable.                                                        |
 | [zendesk__sla_policies](https://fivetran.github.io/dbt_zendesk/#!/model/model.zendesk.zendesk__sla_policies)           | Each record represents an SLA policy event and additional sla breach and achievement metrics. Calendar and business hour SLA breaches are supported.    
@@ -59,10 +61,10 @@ Include the following zendesk package version in your `packages.yml` file:
 ```yml
 packages:
   - package: fivetran/zendesk
-    version: [">=0.13.0", "<0.14.0"]
+    version: [">=0.14.0", "<0.15.0"]
 
 ```
-> **Note**: Do not include the Zendesk source package. The Zendesk transform package already has a dependency on the source in its own `packages.yml` file.
+> **Note**: Do not include the Zendesk Support source package. The Zendesk Support transform package already has a dependency on the source in its own `packages.yml` file.
 
 ## Step 3: Define database and schema variables
 By default, this package runs using your destination and the `zendesk` schema. If this is not where your zendesk data is (for example, if your zendesk schema is named `zendesk_fivetran`), update the following variables in your root `dbt_project.yml` file accordingly:
@@ -74,7 +76,7 @@ vars:
 ```
 
 ## Step 4: Disable models for non-existent sources
-This package takes into consideration that not every Zendesk account utilizes the `schedule`, `schedule_holiday`, `ticket_schedule` `daylight_time`, `time_zone`, `domain_name`, `user_tag`, `organization_tag`, or `ticket_form_history` features, and allows you to disable the corresponding functionality. By default, all variables' values are assumed to be `true`. Add variables for only the tables you want to disable:
+This package takes into consideration that not every Zendesk Support account utilizes the `schedule`, `schedule_holiday`, `ticket_schedule` `daylight_time`, `time_zone`, `domain_name`, `user_tag`, `organization_tag`, or `ticket_form_history` features, and allows you to disable the corresponding functionality. By default, all variables' values are assumed to be `true`. Add variables for only the tables you want to disable:
 ```yml
 vars:
     using_schedules:            False         #Disable if you are not using schedules
@@ -121,7 +123,7 @@ vars:
 *Note: This package only integrates the above ticket_field_history_updater_columns values. If you'd like to include additional updater fields, please create an [issue](https://github.com/fivetran/dbt_zendesk/issues) specifying which ones.*
 
 ### Extending and Limiting the Ticket Field History
-This package will create a row in `zendesk__ticket_field_history` for each day that a ticket is open, starting at its creation date. A Zendesk ticket cannot be altered after being closed, so its field values will not change after this date. However, you may want to extend a ticket's history past its closure date for easier reporting and visualizing. To do so, add the following configuration to your root `dbt_project.yml` file:
+This package will create a row in `zendesk__ticket_field_history` for each day that a ticket is open, starting at its creation date. A Zendesk Support ticket cannot be altered after being closed, so its field values will not change after this date. However, you may want to extend a ticket's history past its closure date for easier reporting and visualizing. To do so, add the following configuration to your root `dbt_project.yml` file:
 
 ```yml
 # dbt_project.yml
@@ -148,7 +150,7 @@ vars:
 ```
 
 ### Changing the Build Schema
-By default this package will build the Zendesk staging models within a schema titled (<target_schema> + `_zendsk_source`), the Zendesk intermediate models within a schema titled (<target_schema> + `_zendesk_intermediate`), and the Zendesk final models within a schema titled (<target_schema> + `_zendesk`) in your target database. If this is not where you would like your modeled Zendesk data to be written to, add the following configuration to your root `dbt_project.yml` file:
+By default this package will build the Zendesk Support staging models within a schema titled (<target_schema> + `_zendsk_source`), the Zendesk Support intermediate models within a schema titled (<target_schema> + `_zendesk_intermediate`), and the Zendesk Support final models within a schema titled (<target_schema> + `_zendesk`) in your target database. If this is not where you would like your modeled Zendesk Support data to be written to, add the following configuration to your root `dbt_project.yml` file:
 
 ```yml
 models:
@@ -212,7 +214,7 @@ A small team of analytics engineers at Fivetran develops these dbt packages. How
 We highly encourage and welcome contributions to this package. Check out [this dbt Discourse article](https://discourse.getdbt.com/t/contributing-to-a-dbt-package/657) on the best workflow for contributing to a package!
 
 ## Opinionated Modelling Decisions
-This dbt package takes an opinionated stance on how business time metrics are calculated. The dbt package takes **all** schedules into account when calculating the business time duration. Whereas, the Zendesk UI logic takes into account **only** the latest schedule assigned to the ticket. If you would like a deeper explanation of the logic used by default in the dbt package you may reference the [DECISIONLOG](https://github.com/fivetran/dbt_zendesk/blob/main/DECISIONLOG.md).
+This dbt package takes an opinionated stance on how business time metrics are calculated. The dbt package takes **all** schedules into account when calculating the business time duration. Whereas, the Zendesk Support UI logic takes into account **only** the latest schedule assigned to the ticket. If you would like a deeper explanation of the logic used by default in the dbt package you may reference the [DECISIONLOG](https://github.com/fivetran/dbt_zendesk/blob/main/DECISIONLOG.md).
 
 # 🏪 Are there any resources available?
 - If you have questions or want to reach out for help, please refer to the [GitHub Issue](https://github.com/fivetran/dbt_zendesk/issues/new/choose) section to find the right avenue of support for you.

dbt_project.yml

@@ -1,5 +1,5 @@
 name: 'zendesk'
-version: '0.13.1'
+version: '0.14.0'
 
 
 config-version: 2

integration_tests/ci/sample.profiles.yml

@@ -16,13 +16,13 @@ integration_tests:
       pass: "{{ env_var('CI_REDSHIFT_DBT_PASS') }}"
       dbname: "{{ env_var('CI_REDSHIFT_DBT_DBNAME') }}"
       port: 5439
-      schema: zendesk_integration_tests_40
+      schema: zendesk_integration_tests_41
       threads: 8
     bigquery:
       type: bigquery
       method: service-account-json
       project: 'dbt-package-testing'
-      schema: zendesk_integration_tests_40
+      schema: zendesk_integration_tests_41
       threads: 8
       keyfile_json: "{{ env_var('GCLOUD_SERVICE_KEY') | as_native }}"
     snowflake:
@@ -33,7 +33,7 @@ integration_tests:
       role: "{{ env_var('CI_SNOWFLAKE_DBT_ROLE') }}"
       database: "{{ env_var('CI_SNOWFLAKE_DBT_DATABASE') }}"
       warehouse: "{{ env_var('CI_SNOWFLAKE_DBT_WAREHOUSE') }}"
-      schema: zendesk_integration_tests_40
+      schema: zendesk_integration_tests_41
       threads: 8
     postgres:
       type: postgres
@@ -42,13 +42,13 @@ integration_tests:
       pass: "{{ env_var('CI_POSTGRES_DBT_PASS') }}"
       dbname: "{{ env_var('CI_POSTGRES_DBT_DBNAME') }}"
       port: 5432
-      schema: zendesk_integration_tests_40
+      schema: zendesk_integration_tests_41
       threads: 8
     databricks:
       catalog: "{{ env_var('CI_DATABRICKS_DBT_CATALOG') }}"
       host: "{{ env_var('CI_DATABRICKS_DBT_HOST') }}"
       http_path: "{{ env_var('CI_DATABRICKS_DBT_HTTP_PATH') }}"
-      schema: zendesk_integration_tests_40
+      schema: zendesk_integration_tests_41
       threads: 8
       token: "{{ env_var('CI_DATABRICKS_DBT_TOKEN') }}"
       type: databricks

integration_tests/dbt_project.yml

@@ -1,12 +1,12 @@
 config-version: 2
 
 name: 'zendesk_integration_tests'
-version: '0.13.1'
+version: '0.14.0'
 
 profile: 'integration_tests'
 
 vars:
-  zendesk_schema: zendesk_integration_tests_40
+  zendesk_schema: zendesk_integration_tests_41
   zendesk_source:
     zendesk_organization_identifier:           "organization_data"
     zendesk_schedule_identifier:               "schedule_data"

models/intermediate/int_zendesk__ticket_schedules.sql

@@ -31,6 +31,7 @@ with ticket as (
             row_number() over (order by created_at) = 1 as is_default_schedule,
             id
           from {{ source('zendesk','schedule') }}
+          where not coalesce(_fivetran_deleted, false)
         )
         select 
           id