AI
Documentation MCP server available (Beta)
If you use AI tools to work with Sigma and want to enrich agent behavior or questions with context about officially supported Sigma functionality, the Sigma documentation can now be accessed using the model context protocol (MCP) server at https://help.sigmacomputing.com/mcp.
For more details about what is and is not supported, and the available tools, see Use the Sigma documentation MCP server.
AI apps
Single-select and multi-select columns in input tables (GA)
Single-select and multi-select columns in input tables are now generally available, except for on Databricks connections, which don't support multi-select columns.
Use single-select and multi-select columns to enable users to add discrete values as follows:
- Single-select: Users can select one value in each row from a predefined list of options. A new selection replaces the existing row value.
- Multi-select: Users can select one or more values in each row from a predefined list of options. New selections are added to the existing row values.
You can manually create and manage a list of distinct and repeatable options, or you can populate the list of options from a column in an existing data source or element in the workbook. Values can then be formatted as pills and assigned different colors for visual differentiation and clarity.
For more information and an interactive demo, see Configure single-select and multi-select columns in input tables.
API
Create and manage data models from code (Beta)
You can create and manage data models programmatically using the Sigma API. The endpoints use a JSON representation of the data model to retrieve contents, make updates, and create new data models. For information on the JSON representation, see Create and manage data models from code.
The following endpoints are now available to read, create, and update data models programmatically:
- Get the JSON representation of a data model (
GET /v2/dataModels/{dataModelId}/spec) - Create a data model from a JSON representation (
POST /v2/dataModels/spec) - Update a data model from a JSON representation (
PUT /v2/dataModels/{dataModelId}/spec)
For example representations of data sources and data model elements, see the Data model representation example library.
New API endpoints available for managing SAML authentication
The following new API endpoints to manage SAML authentication configurations in Sigma are now available:
- List SAML service providers (
GET /v2/saml/service-providers) - Create a SAML service provider certificate (
POST /v2/saml/service-providers/{samlServiceProviderId}/certificates) - List SAML service provider certificates (
GET /v2/saml/service-providers/{samlServiceProviderId}/certificates) - Get a SAML service provider certificate (
GET /v2/saml/service-providers/{samlServiceProviderId}/certificates/{samlServiceProviderCertificateId}) - Activate a SAML service provider certificate (
POST /v2/saml/service-providers/{samlServiceProviderId}/certificates/{samlServiceProviderCertificateId}/activate) - Deactivate a SAML service provider certificate (
POST /v2/saml/service-providers/{samlServiceProviderId}/certificates/{samlServiceProviderCertificateId}/deactivate) - Remove a SAML service provider certificate (
DELETE /v2/saml/service-providers/{samlServiceProviderId}/certificates/{samlServiceProviderCertificateId})
Admins can use these API endpoints to manage SAML authentication certificates used by Sigma as a service provider.
New API endpoint to tag a data model
The following endpoint to tag a data model version is now available:
- Tag a data model (
POST /v2/dataModels/tag)
Admin
Sigma Tenants (Beta)
Set up a multitenant architecture with multiple Sigma organizations to centralize governance while supporting self-contained and isolated tenants. You can create tenants in the same region or different regions.
Example use cases for Sigma Tenants include:
- Comply with data residency requirements with different tenants in different regions
- Fully isolate data for different customers as a managed service provider.
- Centralize governance for multiple business units, but isolate the business units from each other.
Different deployment architectures are supported. Deploy content from the parent organization to tenants or from one tenant to other tenants. See Deploy content to tenant organizations.
Sigma Tenants is a premium feature. For more details, see Sigma Tenants.
Reports
Add and manage multiple report headers and footers (Beta)
You can now create and manage multiple headers and footers for each report.
For more information, see Edit report page setup, headers, and footers (Beta).
Workbook elements
Aggregate table cells by highlighting
You can now aggregate cells in pivot tables by highlighting them. Previously, this ability was only available in level tables. For both pivot and level tables, you can now select from multiple aggregation methods.
For more information, see Working with pivot tables.
Workbook features
Pick from an existing organization locale when adding a workbook locale
When adding a workbook locale, you can now select from a dropdown of existing organization locales, instead of manually entering a custom translation file.
See Add a custom translation for a language.
Run Python code in a document (GA)
Add a Python element to any workbook or data model to write and run Python code. You can run Python code against a connection to Databricks or Snowflake. For setup instructions, see Set up a Databricks connection for Python and Set up a Snowflake connection for Python.
Write Python code that performs complex tasks like data transformation, data analysis, forecasting, prediction, or retrieve and send data to third-party API endpoints. When writing Python in Sigma, you can also:
- Reference data elements like tables, pivot tables, and input tables as DataFrames.
- Incorporate user input into your code by referencing control values.
- Build tables and charts with the output from your Python code.
- Use autocomplete to reference data sources available in your connection.
- Import libraries available in your Databricks or Snowflake account.
Run Python code directly on the Python element, or trigger the code to run from an action. Workbooks with a Python element can be exported and embedded. For more details, see Write and run Python code and Python method reference.
Bug fixes
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Deployment policies with more than 50 documents no longer error.
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When sharing templates from one organization to another, the data sources failed to swap to the correct data source when the data source used OAuth to authenticate to the connection.
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Clicking a pivot table subtotal now correctly passes the subtotal/total value and row/column context into actions (e.g., actions that set control values from the selected subtotal).