> For the complete documentation index, see [llms.txt](https://docs.telm.ai/telmai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.telm.ai/telmai/integrations/atlan-integration.md). # Atlan Integration ## Overview This guide walks you through setting up the Telmai connector in Atlan so that data quality metadata — including DQ dimensions, monitor results, and policy health — surfaces directly on your Atlan assets. Once configured, your data consumers can assess quality without leaving the catalog. The Telmai–Atlan integration embeds quality intelligence directly within the Atlan catalog, so stakeholders can assess data trustworthiness at the point of discovery — without switching tools or second-guessing data reliability. ## Prepare Atlan In Atlan, create a new workflow connector for your data source. This registers your data in the Atlan catalog and is required for the workflow mapping step that follows in Telmai. * Use a recognizable name — e.g., ***Snowflake\_Enterprise*** — for easy reference in the mapping step. ## Prepare Telmai In your Telmai environment, choose the specific connection which points to the assets under consideration — Let's call it ***Snowflake\_DQ***. Ensure it points to the same underlying data source as ***Snowflake\_Enterprise***; this is the pair the workflow will map together. #### Create and Scan an Asset in Telmai Using ***Snowflake\_DQ***, create a new asset — Let's call it ***product\_catalog*** — and run a scan. The sync workflow pulls quality metadata from this scan result. If the asset has never been scanned, the Atlan panel will not display any DQ data after the sync. ## Configure the Telmai Workflow In Atlan, navigate to Workflows → Marketplace. Search for "Telmai" to locate the Telmai connector package. Select it and click Setup Workflow.

Fig. 1 — Atlan Workflow Marketplace: search for "Telmai" to find the Telmai connector.

### Configure Credentials The workflow setup opens on the Credentials tab. Enter your Telmai environment details: * Telmai API URL - Your Telmai environment base URL, e.g. * Telmai Tenant ID - Your tenant identifier — available from your Telmai admin dashboard. * Telmai API Key - Generate or retrieve an API key from your Telmai account settings. * Click Test Authentication to validate before proceeding

Fig. 2 — Step 1: Enter Telmai API URL, Tenant ID, and API Key. Use Test Authentication to verify before moving on.

### Map Connections Click Next to advance to the Connection Mapping step. Here you pair your Atlan connection with the corresponding Telmai connection. * Under Atlan Connection, select ***Snowflake\_Enterprise*** * Under Telmai Connection, select ***Snowflake\_DQ*** * Click Add to Connection Mapping to confirm the pair * Run Preflight Checks - to verify permissions are in place before running. * Click Run (immediate) or Schedule & Run (recurring sync)

Fig. 3 — Step 2: Map Snowflake_Enterprise to Snowflake_DQ, run preflight checks, then Run or Schedule & Run.

## Verify the Integration ### Confirm Asset Visibility and DQ Data in Atlan Once the workflow run completes successfully, navigate to the Assets tab in Atlan and search for the asset ***product\_catalog***. Open the asset detail page, then select the Telmai tab in the right-hand panel to view the synced quality metadata.

Fig. 4 — The Telmai panel on an Atlan asset showing DQ dimension scores, policy results, and the Open in Telmai deep-link.

## Data Quality Metadata in Atlan The Telmai panel on each mapped asset exposes three sections: ### DQ Dimensions A scored breakdown of the asset's quality health across five dimensions (visible in Fig. 4 above):
CompletenessMeasures the percentage of complete records
UniquenessMeasures the percentage of unique records
CorrectnessMeasures the percentage of correct values
FreshnessMeasures how recent the data is
ConsistencyMeasures data consistency across sources
### Policies A summary of monitor results — how many quality monitors passed vs. failed. In the example above (Fig. 4), the asset has 8 policies that failed and created alerts. This headline indicator lets data stewards spot quality regressions without logging into Telmai. ### Open in Telmai A direct deep-link to the asset's full detail page in Telmai — useful for investigating specific dimension failures, reviewing historical trends, or setting up new monitors. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.telm.ai/telmai/integrations/atlan-integration.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.