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Tableau

Prerequisites

  • Curl: Ensure that curl is installed on the system. For Windows systems, curl.exe may be necessary.
  • Lens API endpoint: The API endpoint provided by Lens to sync semantic model, enabling integration with Tableau.
  • Access credentials: Access credentials such as username, password, project name etc., are required for Tableau.
  • DataOS API key: Ensure the DataOS API key is available. Get it by using the following command:
dataos-ctl user apikey get

Steps

To sync the semantic model with Tableau, follow the steps below:

Step 1: Run the curl command

curl --location --request POST 'http://tcp.<DATAOS_FQDN>/lens2/sync/api/v1/tableau-cloud/<WORKSPACE_NAME>:<LENS_NAME>' \
--header 'apikey: <APIKEY>' \
--header 'Content-Type: application/json' \
--data-raw '{
    "project_name": "<SAMPLE>",
    "username": "{USER_NAME/EMAIL}",
    "password": "<PASSWORD>",
    "site_id": "<SITE_ID>",
    "server_address": "https://prod-apnortheast-a.online.tableau.com"
}'

  1. URL:

    • This endpoint is used to sync a specific semantic model to Tableau for public access.
    • Replace with the Fully Qualified Domain Name (FQDN) where Lens is hosted. Example: liberal-monkey.dataos.app.
    • Replace with the name of the workspace where the semantic model (Lens) is deployed. e.g., public, curriculum.
    • Replace with the name of the semantic model to sync. e.g., sales360.

  2. Headers:

    • apikey: User's API key for the current context in Lens. The DataOS API key for the user can be obtained by executing the below command.

      dataos-ctl user apikey get

    • Content-Type application/json: Specifies that the data being sent is in JSON format.

  3. Raw data payload:

    This section defines the details of the user's Tableau credentials and project configuration:

    • project_name: The name of the Tableau project where the data will be synced. Replace "" with the actual project name. If the project does not already exist, Tableau will create a new project with the given name.

    • username: Tableau account username, typically the email ID used to log in to Tableau.

    • password: Tableau account password.

    • site_id: The site ID associated with the current Tableau connection.

    • server_address: The URL of the Tableau server. Replace with the correct server address (e.g., https://prod-apnortheast-a.online.tableau.com). This information can be obtained upon logging in to Tableau. The URL will appear as follows:

      https://prod-apnortheast-a.online.tableau.com/#/site/iamgroot1086a891fef336/home

      Here: iamgroot1086a891fef336 is the site_id.

Step 2: Go to Tableau: Access the Explore tab on the left side. The required tables and views will be visible in the project. In the screenshot below, there are three sources: one for tables and two for views.

Superset Configuration

Step 3: Explore and create visualizations Navigate to the Home tab on the left side and click on 'New'. Under this option, select 'Workbook'.

Superset Configuration

Step 4: Connect to data After clicking on 'Workbook', the 'Connect to Data' page will be displayed. Select either views or tables and click on 'Connect'.

Superset Configuration

Upon clicking 'Connect', a prompt will request the username and password. Enter the DataOS username and API key.

Superset Configuration

Step 5: Start using the semantic model After entering the credentials and clicking on 'Sign In', the model will be ready for visualization purposes.

Superset Configuration

Supported data types

Category Data Type Support Status Recommended Approach
Dimension time Supported NA
Dimension string Supported NA
Dimension number Supported NA
Dimension boolean Supported NA
Measure max Supported NA
Measure min Supported NA
Measure number Supported NA
Measure sum Supported NA
Measure count Supported NA
Measure boolean Auto-converts to Dimension NA
Measure string Auto-converts to Dimension NA
Measure time Auto-converts to Dimension NA
Measure avg Not Supported Option 1: To use measure of type ‘avg’, define an additional measure of type 'count' in that entity:

name: count
type: count
sql: '1'

Option 2: Use measure of type 'number' and define average logic in SQL:

measures:
  - name: total_accounts
    type: number
    sql: "avg({accounts})”
Measure count_distinct Not Supported Option 1: To use measure of type ‘count_distinct’, additionally define a measure of type 'count' in that entity:

name: count
type: count
sql: '1'

Option 2: Or, use measure of type 'number' and define logic for count_distinct in SQL:

measures:
  - name: total_accounts
    type: number
    sql: "count(distinct({accounts}))”
Measure count_distinct_approx Not Supported NA
Rolling Window - Supported NA

Important considerations for Tableau integration

1. Handling Entities without Relationships: An error will occur during synchronization if any entity in the data model lacks a defined relationship. To resolve this issue, the entity can be hidden to avoid synchronization errors.

2. Live connection: The connection between the Lens semantic layer and Tableau Cloud is live meaning that any changes to the underlying data will automatically be reflected in Tableau.

3. Schema changes: If there are schema updates, such as adding new dimensions or measures, the integration steps will need to be repeated to incorporate these changes into Tableau.

4. Avoiding cyclic dependencies: Tableau does not support cyclic dependencies within data models. To prevent integration issues, it is essential to ensure that the data model is free of cyclic dependencies prior to syncing with Tableau.

5. Visualization with multiple data sources: You cannot build a visualization that incorporates data from multiple data sources. For live connections, Tableau does not support data blending. Only a single data source can be used to create a visualization.

6. Centralized management: All data sources should be managed and published by the admin on the server, with everyone else using this source.

7. Single authority for Desktop publications: If data sources are published via Tableau Desktop, ensure that all sources are published by a single authority to avoid multiple data source conflicts on the server.

8. Row limit: The Lens API has a maximum return limit of 50,000 rows per request. To obtain additional data, it is necessary to set an offset. This row limit is in place to manage resources efficiently and ensure optimal performance.

9. Selection: It is important to select fields from tables that are directly related or logically joined, as the system does not automatically identify relationships between tables through transitive joins. Selecting fields from unrelated tables may result in incorrect or incomplete results.

10. Parameter Action: Action filters can be defined on measures/dimensions to filter visualizations effectively.

11. Default chart types: All default chart types provided by Tableau can be plotted and visualized without issues.

12. Rolling Window Measure: For querying a rolling window measure, it is necessary to provide a time dimension and apply a date range filter to this time dimension. When querying a rolling window measure, follow these steps:

  • Select the rolling window measure.
  • Select the time dimension.
  • To define granularity, right-click on the selected time dimension and set granularity (choose a granularity where the complete time, along with the year, is shown).
  • Add the time dimension to the filter, and define the range filter.

Error handling

Scenario 1: Handling syntactical errors in measures or dimensions

If a measure or dimension contains a syntactical error (and is also not functioning in Explore studio of DPH), the following error will appear when attempting to select it:

Superset Configuration

After correcting the syntactical error in the measure or dimension within Lens, the error will no longer appear. To reflect the changes in Tableau, refreshing the data source and re-selecting the measure or dimension will be necessary to display it in the chart.

Superset Configuration

Scenario 2: Handling inactive Lens in the environment

If the Lens is not active in the environment while working on an existing workbook in Tableau or when attempting to establish a new connection, an error will be encountered. This may prevent access to or querying data from the Lens. Verify that the Lens exists and is active before syncing.

Scenario 3: Handling data source errors due to access restrictions

If the Account table is set to public = false, a data source error will occur in Tableau. The error message will indicate that the 'Account table not found,' which will prevent querying or using data from that table.

Superset Configuration

To resolve this issue, ensure the Account table is accessible (set to public = true or assign appropriate permissions) and then resync the Lens in Tableau to regain access.

Governance of model on Tableau Cloud

When the semantic model is activated via BI Sync in Tableau, data masking, restrictions, and permissions set by the publisher are automatically applied, ensuring consistent data security and compliance. The behavior of these policies (e.g., masking) may vary based on the Tableau user.

The Tableau management process involves authentication and authorization using the DataOS user ID and API key when accessing synced data models. This ensures that columns redacted by Lens data policies are restricted based on the user's group permissions.

For example, if a user named iamgroot in the Analyst group is restricted from viewing the 'Annual Salary' column, this column will not be visible in either the Data Product exploration page or Tableau after syncing. Tableau Cloud requires the DataOS user ID and API key for authentication, ensuring that users can access the full model, except for any columns restricted by any data policies. This approach maintains security and guarantees that users only see the data they are authorized to view.