🎉 What's new

You can now use the display name of your custom metadata attributes to update your dbt assets in Atlan!

Atlan now supports two ways to enrich custom metadata for your dbt assets programmatically:

• businessAttributes — supports the existing method of using hashed-string names.
• businessAttributeNames — accepts display names for custom metadata in a human-readable format.

Enjoy additional flexibility to collaborate with key stakeholders as you enrich your dbt assets in Atlan.

Learn more: Change custom metadata on assets

🎉 What's new

Atlan now supports nested columns 15 levels deep for AWS Glue! We've expanded our support from level 1 to level 15 for AWS Glue nested columns, empowering you to go deeper into your data.

✨ Let's dig deeper

Here's what you need to know:

• Atlan retrieves raw STRUCT and ARRAY type objects for AWS Glue nested columns up to 15 levels.
• You can search for and discover nested columns like any other column asset in Atlan.
• You can view nested columns in the column preview and overview sidebar for your table assets.
• You can enrich your nested columns with tags, certificate, description, and more.
• Column-level lineage is supported, so you can view lineage for nested columns on the lineage graph.
• Tag propagation is currently only supported from parent to nested columns.
• Atlan currently does not parse MAP type objects for columns and nested columns.

👏 Give it a shot

Discover and document your nested columns from AWS Glue!

Learn more: What does Atlan crawl from AWS Glue?

🎉 What's new

If you update or rename your Airflow tasks at source, Atlan will delete the old cataloged tasks and associated processes and then reflect the latest state on both the lineage and pipeline graphs. With your data estate always evolving, this release ensures that Atlan is always in sync with your latest updates. The processes created for the task will be updated to reflect these changes as well.

🎉 What's new

Here are some hot-off-the-press improvements and fixes for our dbt users in Atlan:

• dbt test mapping in asset preview and sidebar — we've fixed dbt test mapping in the asset preview card and sidebar. Previously, dbt test results did not display the right environment relationship between the materialized table and dbt test, displaying incorrect information. We've fixed the test mapping to show the correct environment.
• Descriptions for dbt materialized assets — we've updated the way in which Atlan pulls descriptions for materialized tables. If a materialized table is linked to multiple dbt assets, Atlan will apply the description from the linked dbt model to the materialized asset. In case this is unavailable, Atlan will then apply the description from the linked dbt source to the asset.
• Greater visibility for job and model statuses — to provide you with full clarity, Atlan now breaks down job and model status for your dbt materialized tables. You can view the model that materialized a specific table and model status or the job that executed the model as well as job environment and status.
  
  

🎉 What's new

Atlan now crawls Monte Carlo alerts and incidents for the last 30 days by default! This ensures that the red indicators and failing monitors are relevant and actionable, helping you focus on recent and meaningful issues. You'll also have the option to set the date range to the last 14 or 45 days instead of the default configuration.

✨ Let's dig deeper

Previously, Atlan fetched all historical alerts and incidents from Monte Carlo, which often resulted in irrelevant red indicators and failing monitors. For example, an outdated failing monitor from one year ago could show up in Atlan today, causing unnecessary confusion.

Hence, we've optimized the Monte Carlo integration to deliver the following:

• Faster syncs — reduced runtime for the Monte Carlo package, enabling you to schedule your workflows more frequently.
• Fewer API calls — a significant reduction in API requests to avoid any rate-limiting issues with Monte Carlo.

👏 Give it a shot

For any new and existing Monte Carlo integration in Atlan, you'll only receive alerts and incidents for the last 30 days after the next workflow run. You can also modify the configuration to change the data range.

Learn more: How to crawl Monte Carlo

🎉 What's new

Atlan now supports a streamlined experience for discovering and understanding your linked Monte Carlo monitors. Monitors will be categorized by the type of data quality check as shown in Monte Carlo, making it easier for you to understand Monte Carlo metadata for your assets in Atlan. Additionally, we’ve refined the card design to be lighter, highlighting the most critical information at a glance.

🎉 What's new

Atlan now supports column-level lineage between your dbt sources and models! In addition, you'll be able to view dbt column-level processes between assets for more context on lineage. This release builds on the previously released support for column-level lineage for your dbt models.

🎉 What's new

Atlan now supports Looker refinements for views and explores! This release helps you discover refined fields and track lineage across your Looker projects.

✨ Let's dig deeper

Refined fields for views and explores will be displayed with a Refinement label in Atlan, helping you distinguish them from the original assets. You can find this label on each refined field in the sidebar and preview columns.

On the lineage graph, you'll notice an "R" label attached to all refined fields, making it easier to track lineage from dashboards to refined fields in views and explores.

👏 Give it a shot

If you have an existing Looker integration in Atlan, you will need to rerun the crawler to crawl and discover refinements. For any new integrations, these will be available from the start.

Learn more: What does Atlan crawl from Looker?

🎉 What's new

Atlan now supports nested columns for the Azure Cosmos DB for MongoDB connector! This release empowers data teams to discover and enrich their nested columns in Atlan.

✨ Let's dig deeper

To extract columns from Microsoft Azure Cosmos DB collections, Atlan analyzes document schemas, which must be enabled and configured to crawl columns.

Here's what's in store for you with this update:

• Atlan supports nested columns up to level 35 for parent columns.
• Tag propagation is supported from: collections to columns, and parent to nested columns.
• You can search for, view, and enrich your Cosmos DB columns in Atlan. This includes adding descriptions, tags, terms, and more.
• Identify the data type and structure of parent and nested columns.
• Column-level lineage is currently not supported.

👏 Give it a shot

If you have an existing Cosmos DB integration in Atlan, you will need to rerun the crawler to crawl parent and nested columns. For any new integrations, these will be available from the start.

Learn more:

• What does Atlan crawl from Microsoft Azure Cosmos DB?
• How to crawl Microsoft Azure Cosmos DB

🎉 What's new

Atlan now supports crawling hidden datasets from Google BigQuery! This update brings new capabilities to streamline your metadata management and discovery processes in Atlan.

• Catalog hidden datasets — easily crawl hidden datasets by configuring the Google BigQuery crawler in Atlan.
• Discover hidden datasets and lineage — gain insights into hidden datasets and their lineage, enhancing data visibility and traceability across your projects.

Learn more: How to crawl Google BigQuery