Data teams deal with data in all shapes and sizes, but we often get asked about our support for file systems like Parquet, Avro, Iceberg, and more. At Atlan, we know all of your data is important, so that is why with this release we are introducing our integration with Hive to handle these distributed file systems.

Now you can connect to Hive, catalog all of your tables, and view sample data extracted from the table. Once the data is brought in, users can leverage the asset 360° profiles for their Hive assets to assign ownership, apply certificates, tag classifications, associate the proper business terms, and even run queries to further explore the data.

If you’re on an earlier version of Atlan, this connector helps provide a smooth path to migrate and start using Hive in your new instance. For customers starting their journey with Atlan and looking to build a data lakehouse solution, the Hive connector will help accelerate your work.

Who doesn’t love to query data? But what happens when the results are in the wrong order, or you forget to write a sort command in your SQL? Or what if you simply can’t find an item in the results that you're looking for? At Atlan, we never miss a chance to enhance our customers’ user experience.

Now, with just the click of a button, you can sort the data columns in either ascending or descending order. You can also use the search bar to find an item you want and get the results you need. These two capabilities can limit the need to write more SQL in the future and reduce the number of queries needed to get the right results.

Currently, Sort supports NUMBER, TEXT, and BOOLEAN data types, and support for other types is coming soon.

Some of you may have heard about Atlan and dbt partnership a few months ago. Today, we are excited about launching Atlan + dbt for everyone! Now, your team gets 360-degree context about data. 

What does this mean?
Now you can collaborate seamlessly with end-to-end context. Atlan pulls in metrics and models from dbt and maps column-level lineage across your modern data stack, so your data team can work better together. What this will enable:
1. End-to-end, column-level lineage from data source to BI
2. Enable data consumers and producers to self-serve
3. Enforce documentation standards in dbt 

dbt metrics and models as first-class citizens in Atlan:
1. Document your dbt metrics and models
2. Assign owners to business metrics and models
3. Visibility from source to metrics and models

Go beyond tables and warehouses with end-to-end, column-level lineage:
1. View column-level transformations for models
2. Get visibility from your data sources to BI

Enrich dbt documentation with business context:
1. Expose dbt docs to your entire team
2. Bring dbt context into all your tools

Build documentation standards right from dbt:
Atlan’s deep integration with dbt lets you create repeatable, metadata properties — like table owners and verified tags — in your dbt models.
It’s your way of sharing knowledge across your organization, by standardizing documentation for engineers.

Want to learn more? Go here: https://atlan.com/partners/dbt/ 

Disseminating tribal knowledge across the organization is critical for the success and consistency of your data users.  That’s why it’s important to empower the right users in the right environment to help capture this knowledge.

Previously, users with edit access were unable to invite users or update the query collection. This meant that sharing collections was impossible if the query owner leaves or becomes unreachable.

With this release, users who have access to edit a query collection now have more capabilities. While the collection owner still holds the only authority to delete a collection, other members can now invite, update, and manage the collection. All of this ensures that tribal knowledge is captured and maintained even if the query owner leaves or is unavailable.

Organizations continue to look for ways to save money on their cloud data warehouse bills. Atlan is here to be that partner to help organizations reduce those concerns and their bills. In this release, users can now save money while using the data preview feature for all BigQuery table type assets.

Available in the Assets and Insights Tab, users receive a cost nudge informing them of the precise bytes that will be spent during the execution of a query for all assets, such as views, materialized views, and so on.  From there, users can decide if they still want to continue to run the query based on the amount of bytes that will be spent.

Understanding query adoptions without the right visibility can be a challenge.  Have you ever wanted to know:

“How many visual queries have been saved over time?” or

“Who are the top users of Insights in Atlan in the last 30 days”

“How many of my verified visual queries have descriptions added?”

With this release, now you can get the answer to all of your query related questions.

New Widget to monitor Queries saved over time

Keep track of queries saved in Atlan over time for both SQL and Visual Queries.

New section for Scheduled Queries.

Find all scheduled queries setup in Atlan by frequency including the top users scheduling queries.

Granular filters for all your needs

Support has been added for more filter capabilities by Connector & Connection, Query Type, and Time range.  The More Filter bar goes a step deeper with inclusions for Certificate, Terms, Classifications, Properties and Custom Metadata to help you find the exact data you are looking for.

All of this will help monitor the adoption of the insights module better and give visibility to   customers.

When trying to view lineage of different assets in the lineage graph, the ability to search comes in handy. To make that experience much more seamless, we have introduced list based search which will help with quick exploration. 

The assets present in the graph will now show up as a list as soon as you try to search assets in lineage graph. Simply click or type the asset name you are looking for and the asset and associated lineage will be highlighted.

Workflows is a busy place, with connections to create, jobs to run, and the latest runs to monitor.  All of this can be difficult for admins to manage without a single view into all of these activities. To make it easier we have added an overview page to each connection.

The overview page presents you information about the workflow without needing to dig into individual runs or wait for the workflow graph to load.

You can easily get info about your latest runs for the particular workflow, and click into each job run to further analyze.

As an added bonus we now have some cool widgets from reporting center built right into it.  These widgets change based on the type of workflow that you have open in the overview page.

All of this will provide better observation and reporting capabilities at a connection level for the workflow admins.

With this release, you will now be able to download your asset's downstream and upstream impact as a list. This means that when changes are made by you to your asset ownership, you will be able to get context on the downstream impact of the change.

This report will also help in debugging issues that occurred to your asset by performing root-cause analysis on the upstream assets.

We're happy to announce a native connection to SAP HANA, the most popular ERP system.

Configure the connection to your SAP HANA instance from Marketplace and bring your SAP HANA assets into Atlan, enabling governance, lineage, and — with direct connectivity — querying.