Over the past several weeks, we've introduced a set of search IMPROVEMENTS we want to share:

1. Partial title search. Allows users to search for resources by entering just a portion of the title (3+ characters), making it easier to find the right data.
2. More related metadata search. From the context of a resource page, this improvement allows users the ability to search and filter related resources based on all the searchable metadata fields of a resource - including custom fields - which means it is now easier to filter large lists.
3. More camel case support. We have extended camel case support to our relationship filters. This makes it easier to find resources that have complex names that combine uppercase and lowercase letters.
4. Updated column search cards. This update improves the column search experience by providing users with additional information about columns such as database and datatype, making it easier to understand what each resource is without clicking through and back between the detail pages.
   
   
   

At data.world, our goal is to help organizations unlock the full potential of their data. We're constantly improving search in order to better serve our customers looking to take data management and discovery to the next level.

If you're interested in learning more about our data discovery solutions, please visit our website and book a demo. You can also read more about our search features on the docs portal. We look forward to helping you manage your data and transform the way your users discover it!

With the new year comes new features! We are pleased to launch our newest metadata capability: data profiling. This new feature creates metadata describing summary statistics for columns when a collector is run.

These summary statistics will help you understand and trust your data by providing a quick look at the data. For instance, viewing stats like the minimum and maximum values shows the shape of the data, allowing you to know quickly if your data is as expected. 

How can you create profiling metadata? This feature is currently available via the Snowflake, SQL Server, PostgreSQL, and Redshift collectors with more collectors on the near horizon. There are three optional commands that can be used during the collector run to generate the profiling metadata: 

--enable-column-statistics  description: enables harvesting of column statistics

--sample-string-values  description: enables harvesting of histograms for columns containing string data

 --target-sample-size  description: controls the number of rows sampled for computation of column statistics and string-value histograms

You can read more about these commands on the following collector documentation pages:

• Snowflake collector documentation
• SQL Server collector documentation
• PostgreSQL collector documentation
• Redshift collector documentation

We are excited to begin rolling out for preview some exciting ENHANCEMENTS to the user experience on our collections, metadata resources, and glossary pages.

Today, you'll notice a new PREVIEW button on these pages. Click on it to get a preview of some of our latest features.

feature 

• Metadata sections navigation - a table-of-contents-like side menu for easy access to your metadata sections, related resources, etc.
• Collection hierarchy widget - a navigable tree of your data taxonomy.

COMING SOON 

• Relationships UX improvements  - a more information-rich view of the related resources, improved edit/suggest flows.
• Custom icons - dress your custom types in attire that makes sense to you and your catalog users.

To find out more about these new navigation features, please visit our documentation portal.

We are very excited to announce our newest metadata collection feature: Snowflake Tags & Policy harvesting! 

The Snowflake collector can now harvest Snowflake object tags, Snowflake tag-based masking policies, and Snowflake row access policies. This new feature will enhance your data governance experience by allowing you to see if a tag or policy is applied to a table or column coming from Snowflake.

For instance, here is a screenshot from the data.world catalog showing how a Snowflake Tag-Based Masking Policy has been applied to sensitive data columns: routing numbers, bank name, and bank account number. In this view, you can also see the associated Tag (Classification:confidential), and technical details about the Policy, like the Policy Body which explains how the Policy works.

How can you use this new feature? There are 2 optional commands for harvesting this information within the Snowflake collector run. Read more about it in the Snowflake Collector documentation.

Stay tuned for more exciting governance features in the coming months!

Big news today! 🎉

You asked for more granular control of your data catalog and we listened. We're excited to introduce Collection Access Control. This NEW Feature is going to help you scale your Agile Data Governance program by providing more granular ways to control the access and management of your data catalog.

Collection Access Control provides role-based control to your metadata resources by collection, helping you target who can see and edit the resources in your catalog.

Read more about how to manage collection access on our documentation portal.

Custom resources play an important role in a data catalog's ability to accurately represent your company's metadata. Users need to be able to add resources that aren't directly from data sources to give a full picture of their data landscapes. Now, users can create these custom resources directly from the UI and manage them like any other resource.

After designating which resources should have this feature enabled in your metadata profile, users will be able to access these resources in the "Other resources" section in the "New resource" dropdown (in the example below, the custom resources are "Bank account" and Credit card").

For more information, refer to the documentation.

We're pleased to announce our 2nd-generation Monte Carlo collector is now live for beta customers! Monte Carlo is a Data Observability Platform that lets users know about data problems (like broken pipelines), so they can proactively resolve issues. 

The Monte Carlo collector harvests both Incidents and Monitors, which inform users about the issue, when it happened, and where it happened.

For example, users can view relevant information about Incidents and Monitors, like Status, Count, the Date Created, as well as Owner and Severity. You can also open the specific Incident in Monte Carlo directly from the data.world platform. 

You can read more about the newest Monte Carlo collector in our documentation. 

Existing customers, please reach out to your data.world representative to learn more about becoming a beta user.

Quick update! The browse card - a configurable, quick navigation card that directs end-users to a curated starting point - was such a hit with our private instance Enterprise customers that we've extended it so you can configure one for each of your Organization profile pages. Woohoo!

Read our Implementation Guide to get started.

Introducing our newest feature: bulk import and edit for glossary terms!

Catalog administrators can now bulk upload glossary terms for faster onboarding and enrichment, and make bulk edits to ensure your catalog is always accurate.

This feature enables the following workflows:

• upload glossary terms using a template custom to your catalog's metadata profile

• download a spreadsheet of all current glossary terms

• edit information, add new terms, delete terms in exported spreadsheet

• upload updated spreadsheet to application

• preview changes made in spreadsheet before applying changes

For more information, refer to the full documentation here.

We now support metadata collection from Tableau via Connection Manager. Previously, users were able to collect metadata via the data.world Collector, but now users can perform this task in-app.

Both Tableau Online and Tableau Server are supported, as well as the following connection types: Direct connection (inbound), SSH tunnel (inbound, preferred).

For more information, refer to the documentation here.