What’s New in Qlik Cloud

Data Integration

August brings a strong and varied set of updates across Qlik Talend Data Integration. The headline addition is the full Stitch SaaS connector catalogue, opening access to more than 100 pre-built application sources. Elsewhere, Qlik has added deeper Trust Score analysis, more expressive validation rules, tighter data product governance, improved Lakehouse controls, and a new graphical API Designer.

1. Introducing change management for lake landing replication tasks

Lake landing replication tasks now include a dedicated Store changes tab, bringing their change management options closer to those already available for standard replication tasks.

Key capabilities include:

• Change Table capture to store source INSERT, UPDATE, and DELETE operations on the target for incremental downstream processing
• DDL handling controls to either apply source schema changes automatically or ignore them to preserve a fixed Change Table structure
• Before and after images for updated records, with configurable naming suffixes and header column prefixes
• Header column management to exclude unnecessary system metadata or retain the full set for audit purposes
• Flexible full load behaviour, allowing existing Change Tables to be recreated, cleared of previous changes, or retained with their full history

The existing Change Data Partitioning settings have also moved from the General tab into Store changes, keeping related options together.

For teams using lake landing as part of a wider incremental processing architecture. his provides much more control over how changes are captured, structured, and retained.

More information: Store changes settings

2. Qlik Trust Score™ forensic for data products

A new Quality tab within each data product provides a much deeper view of its composite Qlik Trust Score™.

Rather than seeing only the current headline score, users can now explore what is influencing it, how it is changing, and which underlying datasets are driving those movements. The drill-down takes you through the contributing layers, helping you move from the overall score to the root cause of a quality issue in only a few clicks.

This makes the Qlik Trust Score™ more transparent and actionable. Data product owners can identify where attention is needed, while consumers gain a clearer understanding of why a product should be considered trustworthy.

More information: Qlik Trust Score™

3. Advanced expressions and conditional branching in validation rules

Validation rules can now use Qlik script expressions, opening the door to more sophisticated data quality checks without leaving the guided rule builder.

The update adds support for:

• Arithmetic expressions using operators such as +, -, *, /, and modulo
• String and number functions, including Len, Trim, Left, Right, Mid, IsText, IsNum, and Floor
• Parenthesised sub-expressions to control the order in which calculations are evaluated
• Multiple conditions with else if, allowing different validation logic to be applied depending on the data

For example, a rule could validate that fieldA + fieldB = fieldC, or apply different checks depending on the value or type of another field.

Inline expression validation also highlights errors before the rule is saved. Altogether, this gives quality teams much more freedom to build detailed, conditional checks while remaining within the visual interface.

More information: Working with validation rules

4. Request access to data products

Data consumers can now request access to a data product directly from the Data Marketplace when they do not have the required permissions or connections.

Previously, users had to identify the appropriate person within their organisation and request access manually. The new process provides a form within the Marketplace that captures details such as:

• The requester’s name and role
• The reason access is needed
• The required permission level

This creates a clearer, more structured route for requesting governed data access, reducing interruptions for consumers who have found the right data product but cannot yet use its underlying datasets.

More information: Requesting access to spaces

5. Enriched and automated classification through semantic types

Qlik Cloud can now use semantic types to detect and classify sensitive data automatically.

Rather than relying entirely on manual sensitivity declarations, classifications can be applied consistently across datasets wherever recognised semantic types are found.

Fields not covered by a semantic type can still be classified manually, and regulatory requirements can be assigned directly at dataset level.

When a data product is activated, this information is surfaced automatically so consumers can understand any relevant compliance considerations before the product appears in the Marketplace.

This brings sensitivity classification closer to the data itself, helping teams maintain clearer, more consistent governance as datasets and data products evolve.

More information: Managing semantic types

6. Improved header column support for Open Lakehouse streaming tasks

Mind your headers. Qlik Open Lakehouse now provides more control over the metadata columns added to records during streaming ingestion, such as timestamps.

Header column visibility can now be configured across both streaming landing and streaming transform tasks. Within transform tasks, you can choose whether headers are hidden, displayed in the current view, or included in the history view.

The expression builder now also exposes landing headers, making them available for use within transformation expressions. A further setting allows the hdr__from_timestamp column to appear in the current view, supporting partition-based queries where data is partitioned by ingestion date.

Note: These improvements are not supported in Qlik Cloud Government.

More information:
Showing header columns in views
Standard view headers

7. Design, document, and test APIs in Qlik Cloud

A new API Designer brings the main stages of API development into Qlik Cloud, covering design, documentation, and testing within a single graphical experience.

Users can create OpenAPI Specification (OAS/Swagger) or RAML definitions without needing to write the underlying syntax manually. Repository-based sharing also supports collaboration, allowing teams to work together on API projects and maintain their definitions centrally.

Once designed, APIs can be implemented in Talend Studio and deployed, creating a clearer route from API contract through to delivery.

Note: API Designer is not supported in Qlik Cloud Government or Qlik Cloud Government – DoD.

More information: Designing API contracts

8. Full Stitch SaaS connectors catalog now available

The full Stitch SaaS connector catalogue is now natively integrated into Qlik Talend Cloud, adding access to more than 100 pre-built application connectors.

Supported sources include platforms such as Salesforce, Jira, Marketo, and Zendesk, with the catalogue expected to continue growing.

These connectors can be used across several Qlik Talend Cloud scenarios, including:

• Replication tasks
• Data pipeline projects
• Qlik Open Lakehouse

Most connectors are fully certified. A smaller number are classified as Lite, meaning they have been tested against a more limited set of use cases.

This is a substantial expansion of the sources that can be brought into Qlik Talend Cloud without building bespoke integrations. For teams working across a large SaaS estate, it opens a much broader route into governed pipelines and Lakehouse architectures using connectors already available through Stitch.

Note: This capability is not supported in Qlik Cloud Government. Customers using Data Movement Gateway must upgrade to 2025.11.66 or later before creating new tasks with SaaS application connectors.

More information: Supported SaaS applications