🌸 Spring Refresh: Tags, Smarter Search & a Sharper Experience

Hi there,

Since launching Nexadata, we've been focused on building the core capabilities that power enterprise data transformation, mapping, and connectivity. This release shifts that focus to the experience layer. It is shaped directly by feedback from our users, delivering a more intuitive interface, a new organizational layer across the platform, and a set of targeted improvements that make the product feel faster and more cohesive throughout.

🏷️ Global Tag Management

Nexadata now supports a flexible, color-coded tagging system that lets you organize connections, datasets, and workflows without ever leaving your current view.

Tags can be created and applied inline, anywhere in the product. No need to navigate to a settings page before you can use a tag. Create it on the fly, right where you're working, and manage your full tag library centrally from Organization Settings.

Key Capabilities

• Inline tag creation: Create and apply tags in the moment, directly from connections, datasets, or workflows
• Filter by tag: Use tags to filter your views across connections, datasets, and workflows to quickly find what you're looking for
• Color coding: Assign colors to tags to create visual groupings across your workspace
• Central tag management: Maintain a consistent taxonomy across your team from a single location in Organization Settings

📄 View full documentation →

🔍 Smarter Dataset Search and Navigation

We've redesigned the dataset search experience to be faster and easier to use. The updated interface gives you a cleaner, more responsive way to find and navigate your datasets, consistent with the platform's overall look and feel.

🔀 Stack Rows Transformation

The Stack Rows transformation is now available in the pipeline builder. Users can combine two or more datasets by stacking their rows into a single unified output, making it straightforward to consolidate data from multiple sources before passing it downstream in a pipeline.

How It Works

1. Select Stack Rows from the transformation library in the pipeline builder
2. Choose two or more datasets to combine
3. The transformation produces a single stacked output, ready for the next step in your pipeline

📄 View full documentation →

🧱 Platform Fixes

• ENG-885 – Bug Fix: Workflow output configurations now surface a clear error when the selected connection has invalid or expired credentials, rather than failing silently.
• ENG-891 – Bug Fix: Datasets actively referenced in a workflow pipeline can no longer be silently deleted. The platform now blocks deletion and notifies the user that the dataset is in use.
• ENG-892 – Bug Fix: Workflows with a single output pipeline no longer trigger a false column mismatch validation error. Execution now completes as expected.
• ENG-899 – Bug Fix: Connector Copilot datasets that return large result sets now correctly paginate through all results using each API's pagination mechanism. Previously, the connector would stop after the initial response, resulting in truncated data. In addition, error detection during pagination has been improved so that when a pagination failure occurs, users now receive a specific, actionable message rather than a generic error, making it easier to resolve the issue through configuration.

🔭 What's Next

We're continuing to expand Connector Copilot capabilities and investing in smarter dataset configuration. Here's what we're working on:

• OData Support: Connect to OData-compliant APIs natively through the Connector Copilot, without requiring an OpenAPI spec. OData is widely used across major enterprise systems, including SAP S/4HANA and Microsoft Dynamics 365 (spanning both Finance and Sales), making this a significant expansion of out-of-the-box connectivity for enterprise customers.
• Build an Integration from Documentation: Point the Connector Copilot at an API documentation website and let it generate the integration automatically.
• Metadata-Aware Dataset Configuration: Automatically discover and apply metadata from APIs to populate dataset configuration fields during setup.

Thanks for being part of the Nexadata journey!

— The Nexadata Team