> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://help.sigmacomputing.com/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://help.sigmacomputing.com/_mcp/server.

# Migrate to Sigma with an AI assistant (Beta)

> Use migration skills to have an AI assistant rebuild dashboards from Tableau, Power BI, Looker, and other BI tools as Sigma workbooks.

This documentation describes one or more public beta features that are in development. Beta features are subject to quick, iterative changes; therefore the current user experience in the Sigma service can differ from the information provided in this page.

This page should not be considered official published documentation until Sigma removes this notice and the beta flag on the corresponding feature(s) in the Sigma service. For the full beta feature disclaimer, see [Beta features](/docs/sigma-product-releases#beta-features).

You can use migration skills for Sigma to have an AI assistant rebuild your source content — the dashboards, reports, and data models in another business intelligence (BI) tool — as a Sigma document. Each supported source tool has its own skill, and most also have a read-only assessment skill that inventories your existing content so you can decide what to migrate first.

Migration skills allow you to use AI assistants to reduce the time it takes to migrate content to Sigma. Instead of manually reconstructing and verifying your data models by hand, the skills allow an AI assistant to rebuild and verify the content for you. After building the data model, the assistant uses the Sigma MCP server to query it, and compares the results against the same data platform your source content reads from. The migration isn't complete until the values match.

Sigma publishes these migration skills as open source under the Apache 2.0 License. Review the [migration skills notice](/docs/notice-for-migration-skills-for-sigma) before installing or using these migration skills.

## Requirements

* You need an AI assistant that supports skills, such as Claude Code, Cursor, Cortex Code, or Codex.
* You must have [client credentials](/reference/generate-client-credentials) for the [Sigma REST API](/docs/get-started-with-sigmas-api) and the API base URL for your organization,  or authenticate to the [Sigma CLI](/docs/install-and-configure-the-sigma-cli) with OAuth.
* You must have the [Sigma MCP server](/docs/use-sigma-mcp-server) connected in your AI assistant.
* You must have a Sigma [connection](/docs/connect-to-data-sources) to the same data platform your source content queries. Snowflake, Databricks, BigQuery, Redshift, and PostgreSQL connections are supported.
* You must have access to your source tool. Each skill documents the credentials it needs, such as a Tableau personal access token or a Qlik API key.
* You must have Ruby, Python 3, Node.js 18 or later, and Bash installed on your machine.

## Limitations

* Migration skills compare results against your data platform, so the source content must read from a data platform that Sigma can connect to. If the source data exists only in an extract or an imported model, you must load it into your data platform before you migrate.
* The migration skills use the data model code representation and workbook code representation endpoints to recreate Sigma documents. Any limitations that apply to code representation apply to migration skills as well. See [Manage data models as code](/docs/manage-data-models-as-code#limitations) and [Manage workbooks as code](/docs/manage-workbooks-as-code#limitations).

## Supported source tools for migration

Skills are available to help AI assistants migrate from the following source tools to Sigma:

| Source tool               | Skill                    | What it converts                                                      |
| :------------------------ | :----------------------- | :-------------------------------------------------------------------- |
| Tableau                   | `tableau-to-sigma`       | Data sources and workbooks                                            |
| Power BI                  | `powerbi-to-sigma`       | Reports and semantic models, including DAX measures                   |
| Qlik Sense and Qlik Cloud | `qlik-to-sigma`          | Apps, including expressions and set analysis                          |
| ThoughtSpot               | `thoughtspot-to-sigma`   | Models, worksheets, and Liveboards                                    |
| Amazon QuickSight         | `quicksight-to-sigma`    | Analyses and dashboards                                               |
| IBM Cognos                | `cognos-to-sigma`        | Data modules and report specifications                                |
| Looker                    | `looker-to-sigma`        | LookML models and dashboards                                          |
| MicroStrategy             | `microstrategy-to-sigma` | Dossiers, reports, and schemas                                        |
| Sisense                   | `sisense-to-sigma`       | ElastiCube and Live models, and dashboards                            |
| GoodData                  | `gooddata-to-sigma`      | Workspaces, including logical data models, MAQL metrics, and insights |
| Domo                      | `domo-to-sigma`          | Datasets, Beast Mode calculations, and cards                          |

For many source tools, Sigma provides an assessment skill, named `<source-tool>-assessment`, that inventories your existing content and ranks it by complexity. Some source tools have additional skills that move data into your data platform before a migration. For details, see the documentation in the [sigma-migration-skills](https://github.com/sigmacomputing/sigma-migration-skills) repository.

## How the migration skills perform migrations

During a migration, the skills go through the following phases and stop when the AI assistant needs you to make a decision or provide input:

| Phase      | What happens                                                                                                           |
| :--------- | :--------------------------------------------------------------------------------------------------------------------- |
| Assess     | Inventories your source content and ranks it by complexity. This phase is read-only.                                   |
| Discover   | Reads the source model, dashboards, and data platform columns.                                                         |
| Convert    | Translates source measures, calculations, and expressions into Sigma formulas.                                         |
| Data model | Builds a Sigma data model with tables, relationships, and metrics.                                                     |
| Build      | Rebuilds the source pages and visualizations as a Sigma workbook.                                                      |
| Layout     | Applies the workbook layout.                                                                                           |
| Verify     | Uses the Sigma MCP server to query the new Sigma document, queries the source data platform, and compares the results. |
| Security   | Reports any row-level or column-level security found in the source, then applies it after you approve.                 |

## Install the migration skills

Agent skills for migration to Sigma are distributed through the [sigma-migration-skills](https://github.com/sigmacomputing/sigma-migration-skills) repository.

Install only the skills for the source tools you're migrating from, plus the `sigma-authoring` skill. This skill provides the general Sigma reference materials that each source tool's skill relies on.

For example, to install the migration skills as plugins for Claude Code, run the following commands:

```bash
/plugin marketplace add https://github.com/sigmacomputing/sigma-migration-skills.git
/plugin install sigma-authoring@sigma-migration-skills
/plugin install <source-tool>-to-sigma@sigma-migration-skills
```

To use migration skills with another AI assistant, clone the repository and point your assistant at the skill directories you need:

```bash
git clone https://github.com/sigmacomputing/sigma-migration-skills.git
```

For installation steps for other AI assistants, see [Install skills for AI assistants](/docs/install-skills-for-ai-assistants).

## Configure your Sigma credentials

Before your first migration, set the following environment variables so the skills can authenticate to the Sigma REST API:

```bash
# The API base URL for your Sigma organization.
export SIGMA_BASE_URL='<api-base-url>'
# Your Sigma API client credentials.
export SIGMA_CLIENT_ID='<client-id>'
export SIGMA_CLIENT_SECRET='<client-secret>'
# The connection that points at the same data platform as your source content. Optional.
export SIGMA_CONNECTION_ID='<connection-id>'
```

For guidance on identifying your API base URL and generating client credentials, see [Get started with the Sigma REST API](/reference/get-started-sigma-api). The skills also include a setup script that prompts for these values and stores them for you.

## Run a migration

If you're migrating multiple dashboards, start with the assessment skill for your source tool. The assessment is read-only, and produces a ranked list of priorities, so you can migrate the highest-value content first. If you already know which dashboards you want to migrate first, you can skip the assessment.

To start a migration, describe what you want in your own words. The more context you provide, the less the assistant has to guess. Include the source content, the destination folder, the connection to use, and how you want the assistant to handle formulas and security:

Migrate my Power BI report to Sigma.
Source: \[report URL or file path]
Land it in the Sigma folder "\[folder name or ID]".
Use my Sigma connection "\[connection name or ID]". It points at the same data platform the report reads from.

Before you build, tell me whether you're reusing an existing Sigma data model or creating a new one. If the source data isn't in the data platform yet, stop and tell me.

As you build, translate the real measures from the source. If you can't convert a formula exactly, flag it instead of substituting something simpler.

Tell me what row-level and column-level security exists on the source, and wait for my decision before you apply anything.

When you're done, show me the comparison between Sigma and the source, and list anything that didn't carry over.

For example, the assistant asks whether to reuse an existing data model or create a new one, and whether to apply the security it found on the source content.

## Review migrated content

The migration skills verify that certain summary values match between the source tool and the generated Sigma document. However this verification method cannot capture all potential considerations, and AI assistants can make mistakes. Before sharing generated documents with your organization, consider reviewing other details like the following:

* Compare the full Sigma page against the source dashboard. Check the layout, chart types, sort order, and filters
* Ask the assistant to list anything it couldn't convert.
* If you applied row-level or column-level security, check the document as a restricted user as well as an administrator. For more information, see [Impersonate users](/docs/impersonate-users).

If you choose not to apply the row-level or column-level security detected on your source content, everyone with access to the migrated workbook can see every row.

## Related resources

* [Install skills for AI assistants](/docs/install-skills-for-ai-assistants)
* [Use the Sigma MCP Server](/docs/use-sigma-mcp-server)
* [Get started with data modeling](/docs/get-started-with-data-modeling)
* [Get started with the Sigma REST API](/reference/get-started-with-sigmas-api)