What’s New in Qlik Cloud

Data Integration

This month’s update is all about streamlining the developer experience, enhancing trust in AI, and tightening governance across data products and pipelines. With improvements ranging from smarter SQL editing to secure SSH connectivity and AI-aware trust scoring. Qlik continues to make data integration more productive, secure, and intelligent.

1. Smarter SQL with Auto-Complete and Auto-Formatting

Writing SQL just got a whole lot smoother. Qlik Talend Cloud Pipelines now include code auto-completion and formatting for SQL transformations, helping developers move faster and make fewer mistakes. As you type, the editor suggests tables, columns, and SQL keywords, reducing context-switching, guesswork, and typos.

It’s available to all customers. Just start typing and enjoy a cleaner, quicker, neater way to write transformations. Your DBA will thank you.

2. Catalog Filter: “Data” becomes “Datasets”

A small but helpful tweak in the Catalog filter menu. The label “Data” has been updated to “Datasets” to better reflect what’s being filtered. It’s a clearer way to navigate your assets with no change in functionality.

Find out more about browsing datasets from the ‘Catalog’ here.

3. Data Products now retain their model in Qlik Sense

When you create a Qlik Sense app from a data product, the data model defined in Qlik Talend Cloud now comes with it. There is no need to rebuild relationships manually. You’ll see the model in the Data Model Viewer in Qlik Sense, giving you a smoother transition from pipeline to visualisation.

A few things to note:

• Only the data model explicitly defined in Qlik Talend Cloud is included. Sense won’t alter anything extra.
• A previous issue where duplicate column names were automatically renamed has been fixed, so Qlik Sense’s model suggestions now work better with imported models.
• While the model is viewable in both Qlik Talend Cloud and Qlik Sense, it’s not exported as a standalone asset.

This is a nice quality-of-life improvement that helps keep your data product pipelines clean, consistent, and ready for analytics.

4. Data Product Documentation gets a big upgrade

Say goodbye tab-hopping. Qlik now provides a single, comprehensive view of data product documentation, bringing together everything from quality scores and profiling to field descriptions, lineage, and consumption details all in one place.

You can view this “Wikipedia-style” summary directly in the Data Marketplace or export it as a PDF for easy sharing and offline review. It’s a major usability boost that makes life easier for data consumers and ensures the full story behind your data is always just a click away.

Learn about generating the documentation of a data product here.

5. Use Qlik Talend Cloud Rules Directly in Talend Studio

Talend Studio users can now tap into validation rules and semantic types defined in Qlik Talend Cloud, thanks to a new integration component. This means you can apply centrally maintained rules inside Studio without redefining them. This brings better consistency, less duplication, and faster development.

What this means in practice:

• No more copy-pasting rules between platforms
• Validation logic stays consistent across your data landscape
• Centrally governed rules mean fewer errors, faster delivery
• It’s a practical step toward unified, governed data integration — without sacrificing flexibility for developers.

Read more:

Working with validation rules

tDQRules properties

6. New Import Format and Interface for Pipeline Projects

A new, streamlined user interface for importing pipeline projects is now live in Qlik Talend Cloud. Whether you’re importing a project, pulling changes, or retrieving one from version control, you’ll now see clearer controls for assigning key project settings, for instance:

• Database connections for each task
• Target systems
• Cross-project pipeline sources
• Iceberg volume and catalog selections

Behind the scenes, Qlik has also introduced a new export format. Projects now export as a ZIP file containing multiple JSON files, rather than a single JSON file. If you are worried about the old format don’t! It is still supported until January 30, 2026, giving you plenty of time to transition.

Want to convert your existing projects? Just import them and re-export using the new ZIP format.

Note: Projects in the old format can’t be imported via the API.

Read about exporting and importing data pipelines here and exporting and importing replication projects here.

7. Dedicated Menu for Data Product Management

Data product management now has a dedicated menu entry, separate from the Data Marketplace.

This small but meaningful change makes it easier for data product managers to find and manage their products and sets the stage for more improvements in future releases.

More information: Working with data products

8. Secure SSH Tunnel Access for Data Sources

You can now connect to supported data sources via an SSH tunnel, even if you’re not using a Data Movement Gateway. This provides a secure, encrypted way to access data sources behind firewalls, giving you more flexibility in hybrid or restricted network environments.

Currently supported connectors:

• MySQL
• PostgreSQL
• Microsoft SQL Server (CDC-based)

Note: This feature is not supported in Qlik Cloud Government or Qlik Cloud Government – DoD.

Read more: SSH tunnel

9. Qlik Trust Score™ Adds AI-Focused Dimensions

With AI playing an increasingly central role in analytics, Qlik Trust Score™ now includes new dimensions designed to assess the readiness of datasets for AI use. These enhancements help organisations build more reliable models, reduce bias, and ensure their data is both trustworthy and representative.

What’s new:

• Diversity: Measures the breadth and balance of your data, evaluating how well it represents the population or scenario it’s meant to reflect.
• Accuracy: Adds support for custom validation rules under a new “Accuracy” category, with rule severity directly impacting the score.
• Timeliness: Tracks how fresh your data is by comparing actual update patterns against thresholds you define.

These additions strengthen Qlik’s data quality framework, making it easier to identify weak spots before they impact AI outcomes and putting governance front and centre in your AI pipeline.

Learn more about the Qlik Trust Score™ here.