Scheduled action sequences are workflows that run automatically on a schedule, without requiring a user to open or interact with the workbook. You can use scheduled action sequences to periodically send notifications, refresh data, write to input tables, and more.
The following actions can be scheduled:
Notifications and exports
Input table row changes
Stored procedure calls
Python element execution
Scheduled action sequences also support conditional if/else statements, and you can schedule multiple action sequences to run at different frequencies.
The Conditional formatting section has been redesigned to match other formatting options in the editor panel. The change is aesthetic and does not impact any functionality.
When deploying documents to tenant organizations, a document removed from a deployment policy was not redeployed after it was re-added to the deployment policy.
You can create actions that call API endpoints in Sigma workbooks. This allows you to trigger workflows, enrich data, and interact with external systems without leaving Sigma. See Create actions that call API endpoints.
To support the Call API action, you can define API credentials and API connectors directly in Sigma, using diverse authentication methods, dynamic query and path parameters, request bodies with typed variables, and more. You can optionally create a connector from an existing OpenAPI specification. See Configure API credentials and connectors in Sigma.
For step-by-step examples configuring credentials, connectors, and actions to call APIs, see the following tutorials:
The Export data from a workbook (POST /v2/workbooks/{workbookId}/export /) endpoint is now rate limited to 400 requests per minute, instead of 100 requests per minute.
Embeds
New option for workbook:modal:toggle inbound JavaScript event
The workbook:modal:toggle inbound JavaScript event now supports opening a "Save As" modal with a modalType of save-as.
Choose custom category colors from default theme palette
When you customize the colors used for chart color categories, you can now choose colors from the default color palette that is configured for the workbook's current theme.
The ability to add ad hoc calculated rows in pivot tables is now generally available. This allow you to perform one-off calculations in a pivot table row, without modifying the underlying dataset or restructuring your pivot table.
If a workbook uses data from a Snowflake connection, an admin can choose a different virtual warehouse in Snowflake to run the queries in that workbook.
For example, if a few workbooks run complex queries and perform better when run on a large warehouse, you can choose to run only those workbooks on a large warehouse and use a smaller warehouse to run other workbooks.
If you use Sigma Tenants, you can embed content from tenant organizations from the parent organization, without setting up embed credentials for each tenant organization. For details, see Embed content from a tenant organization.
New document:navigateto inbound JavaScript event
A new document:navigateto inbound JavaScript event is now available to navigate to a different data model, report, or workbook in an embed.
You can use the RegexpCount function to return the number of times a regular expression pattern is found in a string. For more information, see RegexpCount.
Sigma has partnered with DataCamp to provide an interactive learning experience, featuring videos, hands-on exercises, and quizzes to help you check your understanding as you practice. You can find it now at Sigma Fundamentals.
Courses include:
Introduction to Sigma
Calculations in Sigma
Visualizations in Sigma
Introduction to AI Apps in Sigma
Data Modeling in Sigma
Try AI before Human Support
Outside of Sigma Support's operating hours, you can chat with our AI chatbot (“Chatbot”) trained on Sigma's public documentation, posts on Sigma Community, and Sigma Quickstarts. The Chatbot, powered by Intercom's FinAI Agent, is available from the Help menu > Live chat > Try AI before Human Support. By interacting with the Chatbot, you agree to Sigma’s AI Chatbot Terms and Privacy Policy. Please do not enter any confidential, sensitive, or personal information into the Chatbot.
Use the Find in table feature to locate specific values in a table or input table. Sigma searches across all visible (not hidden) columns in the element and highlights each match so you can quickly navigate between results using Next and Previous controls.
Errors that occurred on custom SQL elements, pivot table elements, and summary rows in table elements did not produce the workbook:chart:error outbound JavaScript event.
CSV upload using customer-owned cloud storage (Beta)
CSV upload can now use a customer-owned cloud storage data flow instead of the default data flow through Sigma's infrastructure.
When customer-owned cloud storage is enabled, raw and processed CSV files are staged in a customer-owned bucket (instead of a Sigma-owned bucket) before loading to the data platform. Your company controls the bucket region, access, TTL, etc., helping your organization meet security and compliance requirements.
When exporting to cloud storage, you can now generate files directly in Sigma, instead of in your data warehouse. This allows for more supported file types and data platforms, and more reliable export formatting.
When you migrate a dataset to a data model from the Administration > Dataset migration page, related datasets now correctly show that they have been migrated as well.
You no longer need to wait for a dataset migration to complete before starting another migration from the Administration > Dataset migration page.
You can enable audit logs for tenant organizations. When audit logs are enabled for tenant organizations:
Admin users in each tenant organization can review their own audit logs.
Admin users in the parent organization can review audit logs for the parent organization and each tenant organization with audit logging enabled.
Audit logging is not automatically enabled on tenant organizations, even if the parent organization has audit logging enabled. To enable audit logging in a tenant organization, follow the instructions to open a tenant organization as an admin from the parent organization, then enable audit logging.
Configure a BigQuery connection to use OAuth (Beta)
You can now authenticate to BigQuery from Sigma using connection-level OAuth.
Customer managed keys supported for Google Cloud Platform
Sigma now supports the use of customer-managed keys for all GCP regions, allowing you to use your own key management services to encrypt the secrets and data that Sigma uses.
View usage details for Sigma Tenants on the Tenants tab of the usage dashboard.
For example, review the following details:
Organization type: Whether the organization is the parent or a tenant.
Organization name and slug
Total queries performed over the last 90 days
User activity over the last 90 days, such as total users and total active users.
Document activity over the last 90 days, such as number created and number queried.
Embed activity over the last 90 days, such as number of embedded documents and number of embed sessions.
Export and materialization activity, such as total exports and total materializations.
Types of connections in each organization.
Only users with access to view usage dashboards in a parent organization can view the Tenants usage dashboard.
Data modeling
Migrate a dataset to a data model (GA)
Create a data model from a dataset and its links by choosing to migrate a dataset. Optionally choose to update documents that reference the dataset automatically.
When you migrate a dataset, the dataset is unchanged and the contents of the dataset are recreated in the data model. You can also track the status of all datasets in your organization.
For more details about how to migrate a dataset and what is and isn't migrated to the new data model, see Migrate a dataset to a data model.
Validate metrics and relationships in a data model (Beta)
Changes made to metrics and relationships in a data model can affect users that use those metrics and related columns in their documents. If you make changes such as changing columns, deleting metrics, deleting relationships, or swapping sources, you can validate content in the data model to prevent breaking documents that use those metrics and related columns.
Use the form element to create a clear interface for user data entry. Create a form manually, or based on an existing input table or stored procedure.
Forms can submit data to multiple data sources at the same time, and trigger action workflows at the time of submission, allowing you to centrally manage user input in AI apps.
The layout of chart tooltips has been improved. Additionally, a new divider line has been added to certain tooltip configurations to make tooltip values easier to read.
New chart tooltip formatting options available
New formatting options are available for chart tooltips:
Show all column names: You can now choose to hide column names in a tooltip. If Sigma detects that hiding a column name reduces a user's ability to discern between tooltip values, the column name is not hidden in the tooltip.
Show multiple series: For bar, line, and area charts, you can now choose to show a single series or multiple series in the chart tooltip.
Workbook features
Manage locales panel no longer displays default workbook locale
The Manage locales panel in Workbook settings no longer lists the workbook's default locale. Only manually added locales and custom translations now display in the Manage locales panel.
Workbooks that have custom translations added to their default locale still display the locale in the Manage locales panel.
You can configure page background color, background images, and widths at the level of individual pages. These settings override workbook layout and theme settings, enabling more customization options.
With the latest Chrome update to version 144, embedded content with the :responsive_height query string parameter in the embed URL could not be scrolled in an iframe.
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.
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.
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:
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.
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.
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.
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
Deployment policies with more than 50 documents no longer error.
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.
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).
Use other supported IdPs for Databricks OAuth via OAuth token federation
Using OAuth token federation, you can now use other supported identity providers to authenticate to Databricks. Previously, you could only authenticate with Databricks as your identity provider.
The following sections of the product have been renamed:
My documents is now Documents
Shared with me is now Shared with you
The functionality of these sections remains the same.
User profile
Added warning banner for OAuth token expiration
If you access data from a connection that uses OAuth to authorize you, a banner now appears 3 days before your OAuth session expires. You can sign in from the banner to reauthorize your session and avoid losing access to data.
Workbook elements
Create ad hoc calculations (Beta)
Adding ad hoc calculated rows in pivot tables is now supported. This allow you to perform one-off calculations in a pivot table row, without modifying the underlying dataset or restructuring your pivot table.
The repeated container is a layout element that connects to a data source. For each row in the data source, the repeated container generates a layout card, allowing you to quickly generate identical, dynamic layouts from your data.
The single row container is a layout element that connects to a data source. By selecting a key column and value, you can choose a row from the data source to display inside the container, allowing for dynamic, focused views at individual rows.
Add a value list element to create an organized display of details from a data source. You can customize the value list to show custom formula results, control values, static values, and more. When paired with a single row container, you can create a dynamic list that shows individual records from a data based on user input.
File upload columns, controls, and form fields (Beta)
Use file columns in input tables to upload images, documents, and videos directly to Sigma. You can also use file upload controls to select files and upload them to destination input tables.
File columns can accept the following file types, which can be restricted at the column level or in the control properties, if applicable.
Images: JPEG/JPG, PNG, GIF, TIFF, BMP, WebP, SVG
Documents: PDF, CSV, DOC/DOCX, XLS, XLSX, Pages, Numbers, Keynote, JSON, Text file, XML
You can use the Shape setting on an image element to change the shape of an image uploaded to Sigma. For more information, see Image elements.
Workbook features
Copy input table data when swapping sources and applying version tags (GA)
When changing the connection used by input tables in a document or applying a version tag to a document with an input table, you can copy the input table data to the new connection or tagged version.
You can create warehouse views from a tagged version of a workbook or data model. By creating a warehouse view from a tagged version, you can maintain a stable query for a virtual table in your warehouse, regardless of changes made to the published version. For more information, see Use warehouse views with version tagging.
Bug fixes
Custom page headers now span the full workbook width, instead of matching the selected page width.
Tagging a workbook or data model version updates the owner of the tagged version to the user who tagged the version of the document.
When tagging a workbook version that uses a data model as a source, selecting the checkbox to Allow user to use data sources when they "Save as" resulted in an error: "Error: Cannot grant access to Hidden inodes".
As part of this change, if you select Allow user to use data sources when they "Save as" when tagging a workbook that uses a data model as a source, you must manually grant access on any data models used in the workbook to any users or teams with whom the tagged workbook version is shared.
You can now export to an external stage when configuring ad hoc and scheduled cloud storage exports. For more information, see Export to cloud storage.
Bug fixes
Updated metrics from Snowflake semantic views to use correct metrics syntax when referenced in the formula bar.
When migrating a dataset that contained a SQL statement that used a user attribute to reference a data model, users received an error indicating "There is a cycle in this element's dependencies" and referenced workbooks were not updated.
Sigma now creates edit logs (also known as write-ahead logs or WALs) at the individual input table level and stores each edit log in the same schema as its corresponding input table data.
For non-OAuth connections, edit logs continue to use the same user configurations or service account credentials to access and write to the destination schema. OAuth connections, however, no longer require a service account and instead use the same OAuth credentials to write input table data and the corresponding edit log.
For chart interactions, data is now correctly scoped in the Selection action variable. By including values from all columns relevant to a chart selection and excluding values that are not applicable, this fix addresses formula evaluation errors and unexpected variable output.
The Update row(s) action in a version tagged workbook now references the correct workbook ID (that of the tagged version instead of the published version) to run as expected.
When migrating a dataset, the migration tool attempted to migrate deleted datasets that referenced the dataset.
When migrating a dataset joined to another dataset sourced from SQL, the SQL was not migrated to the new data model.
