As a leading BI platform, Tableau is widely used by organizations to gain insights and make business decisions. However, finding the right Tableau dashboard or worksheet can be challenging due to unclear names or a lack of context. 

To address this issue, we are introducing a preview for Tableau dashboards and worksheets in Atlan. This feature allows you to quickly preview a dashboard or worksheet in a single click directly within Atlan, providing the context you need to confidently select the right asset.

We recently released Atlan Playbooks to minimize human intervention and automate data curation and documentation tasks. Data teams can use Playbooks to create automation rules for bulk tagging, owner assignments, column descriptions, classifications, and more, thereby reducing the time and effort spent on manual processes. 

At the same time, the ability to leverage custom metadata is one of the core value propositions of using Atlan. So why not use both Playbooks and custom metadata?

That is exactly what we did in our latest update to Atlan Playbooks. Data teams can now use Playbooks to perform bulk updates on custom metadata fields. For instance, if there is a custom metadata field for the data steward, users can automatically assign “John” as the data steward for all properties at once, eliminating the need for manual updates. 

One of the core principles of the Atlan platform is to automate wherever possible.  With great automation features like Trident suggestions, Google sheets, and Playbooks, documenting and enriching metadata across your data estates becomes more scalable. Now, with a new Automation dashboard, tracking the impact that automations have on your data estate just got that much easier.

The all-new Automations dashboard provides insights into the updates made across your data estate using Atlan’s automation features.

With the Automation dashboard quickly understand:

• How many trident suggestions were accepted or who were the top trident users over the last 14 days?
• Which assets were updated using playbooks during that same time period?
• What type of updates to certifications were made using the Google sheets add-on?

This new dashboard helps teams evangelize Atlan’s contributions to document enrichment and improve the context for data assets across your data estate.

We created the Reporting Center to give organizations a bird’s eye view of all the metadata updates in Atlan through visualizations that help you track adoption, curation, and metadata management. We are always looking to improve the customer experience through insights displayed and support for the variety of asset types organizations work with.

With this release, we are adding two new enhancements to the Reporting Center.

Better enrichment tracker: Users can now sort on the enrichment tracker to find top performers for the metadata updates they care most about.  Or simply filter data to see how Trident suggestions helped users curate metadata on your data assets.

Support for Database & Schema filters on the Insights dashboard: We now support database and schema level filtering in the insights dashboard. Just select a connection to see the option pop up and start filtering away to your heart's desire!

Sigma is a cloud analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. At Atlan we are always looking to support more use cases from more sources, giving data teams the context they need across their entire data estate.

With this new Sigma connector, users can:

• Discover all of their Sigma assets (workbooks, workbook pages, data elements, data element fields, datasets, and dataset columns) in Atlan.
• Gain visibility into column-level lineage from Sigma datasets, elements, and workbooks back to the data source to solve use cases like root cause analysis.
• Open a related Sigma workbook directly from inside Atlan for quick access and analysis.

This integration also surfaces SQL queries associated with Sigma Data Elements into Atlan as metadata.  This allows users to edit and tweak that same SQL query using Atlan Insights to fit their own use cases. From there, the query can then be saved in Atlan as an asset and leveraged in the future for other needs.

Databricks users are passionate about the platform and its capabilities, so why force them to leave a product they love to find information about their data assets?  We previously released the Atlan Chrome extension to help users across a variety of BI and cloud data warehouse tools get access to the right context about data assets without having to leave their tools of choice.  With this latest update, we're now extending the same convenience to Databricks.

Before this update, accessing data assets in Atlan required logging in, searching through databases, schemas, tables, or columns, and then manually finding the context or documentation required. 

But now, with this update, you can access all that information in just one click, by using the Atlan Chrome extension to open Atlan's sidebar directly in your Databricks instance, providing you with all the context you need without ever leaving your Databricks environment.

How often has your data analyst made a change to a data model, only to get a message a few hours later that the marketing or sales dashboard is broken?  How can we minimize this risk while also providing transparency for the data engineer and data consumer?

With this release, we are bringing the power of active metadata from Atlan to GitHub. Users can now access all the context they need to minimize the risk for data consumers.

Now whenever someone opens a pull request in GitHub to change a dbt model, the Atlan-GitHub action will automatically create a list of all downstream assets that will be impacted by this request.  This gives them the visibility they need to understand the impact before they make the change.

To set up the Atlan - GitHub integration, just got and install the Atlan action from the GitHub marketplace in their dbt GitHub repo.

The ability to leverage custom metadata is one of the core value propositions of using Atlan. While Atlan has supported custom metadata for tools like Airflow, data quality tools like Great Expectations, and more, the visibility around the metadata was easy to miss.    

The custom metadata was available in a separate tab in the Atlan sidebar, meaning users must search to find the appropriate information.  We wanted to make it easier for admins and data teams to provide more visibility into the most critical custom metadata information.

With the introduction of customer metadata badges, admins now have the flexibility to highlight the specific customer metadata information they want right within the Asset overview.  Users can instantly understand if an Airflow DAG was successfully run for this asset or if a table's data quality has failed.  Custom metadata badges will help provide a faster and easier way for users to consume the metadata and get the context they need.

A foundational value of any metadata platform is enabling data teams to curate and organize data sets so that they can be consumed by people looking for the right level of information.  Unfortunately, the process of curation can be a tiresome manual process to ensure that data sets have the right level of documentation in place, data owners are identified, and business context is associated with these data sets.

With the massive amounts of data organizations deal with, manual data curation, at scale and in a repetitive manner, is not a feasible approach.

Atlan help shifts this paradigm by limiting the scale of human intervention and leveraging automation to help map your data estate.  In this release, we are Introducing Atlan Playbooks, a low/code - no/code metadata automation for your data estate. 

Using Atlan Playbooks data teams can create rule-based automation to bulk-create tags, attach owners, propagate column descriptions, attach classifications, and more, to reduce manual processes they face on a daily basis.

Understanding how a simple change to one asset can impact assets downstream is critical to the stability and trust of the business.  One change to a dataset upstream can create chaos in downstream data pipelines and dashboards, resulting in a disruption to the business.

With this release, you can fetch your data asset’s downstream impact in Google Sheets. This will help users get context on the downstream impact when any change is made on the upstream asset.