Change sisense references for internal analytics to tableau

doc/development/internal_analytics/index.md

@@ -64,28 +64,48 @@ On our SaaS instance both individual events and pre-computed metrics are availab
 Additionally for SaaS page views are automatically instrumented.
 For self-managed only the metrics instrumented on the version installed on the instance are available.
 
+### Events
+
+Events are collected in real-time but processed in an asynchronous manner.
+In general events are available in the data warehouse at the latest 48 hours after being fired but can already be available earlier.
+
+### Metrics
+
+Metrics are being computed and sent once per week for every instance. On GitLab.com this happens on Sunday and newest values become available throughout Monday.
+On self-managed this depends on the particular instance. In general, only the metrics instrumented for the installed GitLab version will be sent.
+
 ## Data discovery
 
-The data visualization tools [Sisense](https://about.gitlab.com/handbook/business-technology/data-team/platform/sisensecdt/) and [Tableau](https://about.gitlab.com/handbook/business-technology/data-team/platform/tableau/),
-which have access to our Data Warehouse, can be used to query the internal analytics data.
+Event and metrics data is ultimately stored in our [Snowflake data warehouse](https://handbook.gitlab.com/handbook/business-technology/data-team/platform/snowflake/).
+It can either be accessed directly via SQL in Snowflake for [ad-hoc analyses](https://handbook.gitlab.com/handbook/business-technology/data-team/platform/#snowflake-analyst) or visualized in our data visualization tool
+[Tableau](https://about.gitlab.com/handbook/business-technology/data-team/platform/tableau/), which has access to Snowflake.
+Both platforms need an access request ([Snowflake](https://handbook.gitlab.com/handbook/business-technology/data-team/platform/#warehouse-access), [Tableau](https://handbook.gitlab.com/handbook/business-technology/data-team/platform/tableau/#tableau-online-access)).
 
-### Querying metrics
+### Tableau
 
-The following example query returns all values reported for `count_distinct_user_id_from_feature_used_7d` within the last six months and the according `instance_id`:
+Tableau is a data visualization platform and allows building dashboards and GUI based discovery of events and metrics.
+This method of discovery is most suited for users who are familiar with business intelligence tooling, basic verifications
+and for creating persisted, shareable dashboards and visualizations.
+Access to Tableau requires an [access request](https://handbook.gitlab.com/handbook/business-technology/data-team/platform/tableau/#tableau-online-access).
 
-```sql
-SELECT
-  date_trunc('week', ping_created_at),
-  dim_instance_id,
-  metric_value
-FROM common.fct_ping_instance_metric_rolling_6_months --model limited to last 6 months for performance
-WHERE metrics_path = 'counts.users_visiting_dashboard_weekly' --set to metric of interest
-ORDER BY ping_created_at DESC
-```
+#### Checking events
 
-For a list of other metrics tables refer to the [Data Models Cheat Sheet](https://handbook.gitlab.com/handbook/product/product-analysis/data-model-cheat-sheet/#commonly-used-data-models).
+Visit the [Snowplow event exploration dashboard](https://10az.online.tableau.com/#/site/gitlab/views/SnowplowEventExplorationLast30Days/SnowplowEventExplorationLast30D?:iid=1).
+This dashboard shows you event counts as well as the most fired events.
+You can scroll down to the "Structured Events Firing in Production Last 30 Days" chart and filter for your specific event action. The filter only works with exact names.
+
+#### Checking metrics
+
+You can visit the [Metrics exploration dashboard](https://10az.online.tableau.com/#/site/gitlab/views/PDServicePingExplorationDashboard/MetricsExploration).
+On the side there is a filter for metric path which is the `key_path` of your metric and a filter for the installation ID including guidance on how to filter for GitLab.com.
 
-### Querying events
+### Snowflake
+
+Snowflake allows direct querying of relevant tables in the warehouse within their UI with the [Snowflake SQL dialect](https://docs.snowflake.com/en/sql-reference-commands).
+This method of discovery is most suited to users who are familiar with SQL and for quick and flexible checks whether data is correctly propagated.
+Access to Snowflake requires an [access request](https://handbook.gitlab.com/handbook/business-technology/data-team/platform/#warehouse-access).
+
+#### Querying events
 
 The following example query returns the number of daily event occurrences for the `feature_used` event.
 
@@ -100,7 +120,23 @@ AND app_id='gitlab' -- use gitlab for production events and gitlab-staging for e
 GROUP BY 1 ORDER BY 1 desc
 ```
 
-For a list of other event tables refer to the [Data Models Cheat Sheet](https://handbook.gitlab.com/handbook/product/product-analysis/data-model-cheat-sheet/#commonly-used-data-models-2).
+For a list of other metrics tables refer to the [Data Models Cheat Sheet](https://handbook.gitlab.com/handbook/product/product-analysis/data-model-cheat-sheet/#commonly-used-data-models).
+
+#### Querying metrics
+
+The following example query returns all values reported for `count_distinct_user_id_from_feature_used_7d` within the last six months and the according `instance_id`:
+
+```sql
+SELECT
+  date_trunc('week', ping_created_at),
+  dim_instance_id,
+  metric_value
+FROM common.fct_ping_instance_metric_rolling_6_months --model limited to last 6 months for performance
+WHERE metrics_path = 'counts.users_visiting_dashboard_weekly' --set to metric of interest
+ORDER BY ping_created_at DESC
+```
+
+For a list of other metrics tables refer to the [Data Models Cheat Sheet](https://about.gitlab.com/handbook/product/product-analysis/data-model-cheat-sheet/#commonly-used-data-models).
 
 ## Data flow
 
@@ -131,8 +167,8 @@ flowchart LR;
         end
     end
     snowplow[\Snowplow Pipeline\]
-    snowflake[(Data Warehouse)]
-    vis[Dashboards in Sisense/Tableau]
+    snowflake[(Snowflake Data Warehouse)]
+    vis[Dashboards in Tableau]
 ```
 
 ## Data Privacy

doc/development/internal_analytics/metrics/metrics_dictionary.md

@@ -162,7 +162,3 @@ To use a metric definition to manage [performance indicator](https://about.gitla
 [Metrics Dictionary is a separate application](https://gitlab.com/gitlab-org/analytics-section/analytics-instrumentation/metric-dictionary).
 
 All metrics available in Service Ping are in the [Metrics Dictionary](https://metrics.gitlab.com/).
-
-### Copy query to clipboard
-
-To check if a metric has data in Sisense, use the copy query to clipboard feature. This copies a query that's ready to use in Sisense. The query gets the last five service ping data for GitLab.com for a given metric. For information about how to check if a Service Ping metric has data in Sisense, see this [demo](https://www.youtube.com/watch?v=n4o65ivta48).

doc/development/internal_analytics/metrics/metrics_lifecycle.md

@@ -33,12 +33,12 @@ Currently, the [Metrics Dictionary](https://metrics.gitlab.com/) is built automa
 ## Remove a metric
 
 WARNING:
-If a metric is not used in Sisense or any other system after 6 months, the
+If a metric is not used in Tableau or any other system after 6 months, the
 Analytics Instrumentation team marks it as inactive and assigns it to the group owner for review.
 
 We are working on automating this process. See [this epic](https://gitlab.com/groups/gitlab-org/-/epics/8988) for details.
 
-Analytics Instrumentation removes metrics from Service Ping if they are not used in any Sisense dashboard.
+Analytics Instrumentation removes metrics from Service Ping if they are not used in any Tableau dashboard.
 
 For an example of the metric removal process, see this [example issue](https://gitlab.com/gitlab-org/gitlab/-/issues/388236).
 

doc/development/internal_analytics/service_ping/index.md

@@ -43,7 +43,7 @@ We use the following terminology to describe the Service Ping components:
 
 ## Service Ping request flow
 
-The following example shows a basic request/response flow between a GitLab instance, the Versions Application, the License Application, Salesforce, the GitLab S3 Bucket, the GitLab Snowflake Data Warehouse, and Sisense:
+The following example shows a basic request/response flow between a GitLab instance, the Versions Application, the License Application, Salesforce, the GitLab S3 Bucket, the GitLab Snowflake Data Warehouse, and Tableau:
 
 ```mermaid
 sequenceDiagram
@@ -53,7 +53,7 @@ sequenceDiagram
     participant Salesforce
     participant S3 Bucket
     participant Snowflake DW
-    participant Sisense Dashboards
+    participant Tableau Dashboards
     GitLab Instance->>Versions Application: Send Service Ping
     loop Process usage data
         Versions Application->>Versions Application: Parse usage data
@@ -70,7 +70,7 @@ sequenceDiagram
     Versions Application->>S3 Bucket: Export Versions database
     S3 Bucket->>Snowflake DW: Import data
     Snowflake DW->>Snowflake DW: Transform data using dbt
-    Snowflake DW->>Sisense Dashboards: Data available for querying
+    Snowflake DW->>Tableau Dashboards: Data available for querying
     Versions Application->>GitLab Instance: DevOps Score (Conversational Development Index)
 ```