Announcing Collate 1.7

We are excited to announce Collate Release 1.7, a transformative update for our managed OpenMetadata services. This new release uses AI and intelligent automation to tackle the challenges of tedious data management head-on. At the heart of this release sits Collate AutoPilot, a suite of AI agents designed to dramatically accelerate data service onboarding and automate ongoing operations. These agents work tirelessly in the background, handling manual documentation, classification, and quality testing tasks that traditionally consume countless human hours.

Complementing AutoPilot is our innovative Reverse Metadata capability, which breaks down the one-way barrier that limits other data management tools. Metadata captured in Collate — such as descriptions, tags, and ownership — can now be automatically synchronized back to your source systems, promoting consistency across your entire data ecosystem without manual intervention.

Release 1.7 doesn't stop there. Building on the latest innovations from the open source OpenMetadata project, we've enhanced the user experience with customizable personas, advanced lineage visualizations, more powerful search capabilities, and expanded connector options. Together, these improvements deliver unprecedented automation, customization, and governance capabilities for modern data teams. Keep reading to discover how Collate 1.7 frees data professionals from routine maintenance tasks, empowering them to focus on turning data into business value.

AutoPilot Uses AI Agents to Accelerate Onboarding New Services

Collate AutoPilot’s AI Agents automatically document, tier, and quality test your data for enhanced data governance and insights

Collate 1.7 marks the debut of the Collate AI AutoPilot application, a breakthrough enhancement to Collate AI to automate manual metadata management tasks and, saving time for data teams.

AutoPilot’s new Metadata Ingestion Agent automatically extracts comprehensive metadata from your data sources, while three new AI Agents help manage that metadata:

1. The Documentation Agent automatically builds descriptions based on the shape of your data and generates SQL queries from natural language requests (Text2SQL).

2. The Tiering Agent analyzes your organization’s table usage and lineage to determine the business criticality of each data asset, and prioritizes them in tiers.

3. The Data Quality Agent validates tables' patterns and constraints to intelligently create data quality tests to catch issues before they impact business decisions

These agents not only run during initial data onboarding, but are also scheduled on an ongoing basis for continuous maintenance. The impact of these agents are seen through the enhanced Service Insights Dashboards, which show PII and tiering distribution, query cost optimizations, data quality health, most used data assets, and more. Together, the Collate AI Agents in AutoPilot work like additional team members, saving you time and resources. You can learn more about Collate AI AutoPilot in this blog post.

Activating your Metadata Across Systems with Reverse Metadata

Collate 1.7's Reverse Metadata application pairs with source system capabilities (Snowflake’s Masking Policy via tags shown here) to create a powerful centralized approach to data policy management.

Collate's collaboration and automation features make it simple to add tags, descriptions, and owners to all your data assets. But how can you ensure this metadata is made available and kept consistent with your other data services?

Reverse Metadata is a new application in Collate 1.7 that lets you send descriptions, tags, and owners collected in Collate back into their data sources. You have granular control over which assets you want to monitor for changes to sync metadata back to the data sources, as well as the ability to configure the specific fields that you want updated in real time. Systems supported include Athena, BigQuery, Clickhouse, Databricks, Microsoft SQL Server, MySQL, Oracle, Postgres, Redshift, Snowflake, and Unity Catalog.

Pairing this feature with key capabilities of the source system, such as Snowflake’s ability to handle Masking Policies based on tags, creates a powerful approach to centralize policy management in Collate. Linking this application to other Collate features, such as Metadata Automations or Auto Classification workflows, makes Collate a key pillar in your end-to-end automated data governance strategy. You can see it in action in this short demo video:

What’s New in OpenMetadata 1.7

In addition to the improvements noted above, Collate Release 1.7 also includes all the powerful features introduced in the latest OpenMetadata 1.7 open source release:

• Persona customizations: Tailor the OpenMetadata user experience for different user personas with customizable navigation panels, tabs, and widgets.

• Improved user experience: Streamlined navigation, redesigned asset pages and restructured user pages for faster data discovery and actionability.

• Search Relevancy Settings: Customize the data discovery experience by controlling field matching, default boosting, and asset-specific settings.

• Enhanced lineage layers: Explore data flows with new service and domain layers, along with an enhanced toolbar and minimap for navigating large lineage diagrams.

• New connectors: Expanded ecosystem of 93 connectors, with new integrations for OpenSearch, Cassandra, and CockroachDB, as well as a WhereScape connector for Collate.

Learn more in the OpenMetadata 1.7 Release blog.

Get Started

Check out Collate Release 1.7 and try out the new features for yourself by signing up for Collate’s Free Tier — or test them with demo data in the product sandbox. To learn more about Collate and OpenMetadata:

• Read the how-to guides

• Watch our demo videos

• Join the Slack community