What’s New in Qlik Cloud

Data Integration

November’s updates are bursting with new features for SQL developers, data product managers, and pipeline architects alike. Including enhanced validation rules to a redesigned SQL editing experience, it proves Qlik is continuing to refine the data integration workflow. Expanded support for Databricks, JSON data types, and Trust Score visibility ensures your pipelines stay powerful, governed, and ready for scale.

1. Import a project from version control in Pipelines

You can now import a project branch directly from version control into Qlik Talend Cloud. This makes reviewing a colleague’s work, sharing assets across dev and prod spaces, or testing changes in isolation a breeze.

An intuitive wizard walks you through selecting the repository, branch, and base path, then helps configure source/target connections and task settings.

To get started, head to your project page and hit ‘Create new’.

Learn more: Importing a project from version control

2. Knowledge marts are now supported on Databricks

Qlik Talend Cloud continues to extend its AI and vector search capabilities with support for Knowledge Mart and File-based Knowledge Mart tasks on Databricks.

This means you can now transform and vectorise structured data into domain-specific documents, ready for semantic search and RAG (retrieval-augmented generation), using Databricks as your compute and vector store platform.

Whether you’re building intelligent assistants or enriching enterprise search, Databricks is now part of the toolkit.

What’s new:

• Databricks Vector Store is now a supported destination
• Databricks LLMs are now supported for embedding

Still supported:

• Vector stores: Snowflake Cortex, Elasticsearch, OpenSearch, Pinecone
• LLMs: OpenAI, Azure OpenAI, Amazon Bedrock, Snowflake Cortex

The reach of Knowledge Marts is growing, and with it your freedom to build AI-powered applications on the stack that suits you.

Learn more: Creating knowledge marts

3. New SQL transformation UI

Qlik Talend Cloud now features a completely redesigned SQL editor, purpose-built to support more advanced, efficient transformation work.

This new interface gives SQL developers a modern, fluid experience with:

• Expanded workspace for writing queries, including support for multiple queries in one editor and the ability to run selected statements individually
• An updated dataset panel showing both current and historical versions, with automatic SELECT statement generation
• Keyboard shortcuts to speed up common actions (run query, comment lines, search and replace, and more)
• Visibility of the last executed query and runtime helping you fine-tune performance
• Automatic parameterisation of datasets for quicker setup

You’ll still benefit from all the features you’re used to: syntax highlighting, auto-complete, formatting, undo/redo, and the SQL Assistant in a new sharper, developer-friendly experience.

This is more than a UI tweak; it’s a meaningful upgrade for anyone building serious pipelines.

Learn more: Adding SQL transformations

4. Semantic Types Now Show Dataset Coverage

A new addition to the Data Quality section makes it easier to understand the reach of your semantic types. Semantic types are pattern-based classifications – such as email addresses, phone numbers, or national IDs – used to detect and validate the kind of data a field contains.

Each semantic type now displays a count of the datasets where it has been discovered. This quick visibility helps you gauge how widely patterns are applied across your estate and gives useful context when updating or removing a type.

Whether you’re managing quality rules or assessing reuse across projects, this small change adds a valuable layer of impact analysis.

Note: Not supported in Qlik Cloud Government or Qlik Cloud Government – DoD.

Learn more: Managing semantic types

5. Validation Rules: Now with Time-Aware Operators

You can now create smarter validation rules that compare date or date/time values against a relative time window.

New binary operators include:

• is in the last
• is not in the last
• is in the next
• is not in the next

These additions allow you to check whether a field value falls within (or outside) a defined period, like the last 30 days or the next 2 weeks. This makes it easier to enforce rules that check how recent a value is, whether it has expired, or if it relates to a future deadline. It’s a powerful step in making data quality rules more expressive and time sensitive.

Learn more: Working with validation rules

6. Qlik Trust Score™ is now available at data product level

You can now view the Qlik Trust Score™ directly in the overview of each data product, giving you a faster, clearer read on reliability without diving into individual datasets.

Alongside this, the data product page has had a tidy-up to help you find what you need faster. You’ll now see:

• A dedicated description tile for quick context
• New usage and activity tiles to track adoption
• An improved dataset list that includes the Qlik Trust Score™, last score computation date, and richer data quality insights

A subtle but welcome lift to everyday usability, and a little less clicking around.

Learn more:
Qlik Trust Score™
Working with data products

7. OData-Compliant APIs now supported in Qlik Cloud Government

Data Product Managers in Qlik Cloud Government can now expose their data products through secure, OData-compliant API endpoints, making it easier to share data across teams, tools, and partners.

What this unlocks:

• Seamless integration: Connect data products to BI tools, analytics platforms, and enterprise apps without the need for custom connectors
• Faster access to insight: OData support means analysts and developers can query, filter and use data straight away
• Governed and secure: Endpoints respect existing permissions and access controls, so security policies remain intact

By supporting this widely adopted standard, Qlik makes it simpler to extend the reach of your data products, whether for internal dashboards, automated workflows, or external collaboration.

Learn more: Consuming data products through APIs

8. Validation rules suggestions in Qlik Talend Cloud

Qlik Talend Cloud now offers automatic suggestions to help you get started with validation rules more quickly. Based on your dataset, it recommends rules, including multi-field checks, to streamline the process and improve data quality with less manual effort.

Note: Not supported in Qlik Cloud Government or Qlik Cloud Government – DoD.

Learn more: Working with validation rules

9. Enhanced datetime precision control

You can now view and adjust the precision of datetime fields in data integration projects. This added flexibility is also available in transformation flows, where the dates processor includes new configuration options to fine-tune datetime precision as needed.

Learn more: Dates processor

10. Automatic mapping of JSON data types to compatible targets

JSON columns from SaaS application sources are now automatically mapped to compatible data types on the target when using replication or lake landing tasks.

This is controlled via the new Map compatible source JSON columns to JSON columns on the target setting, which is enabled by default for new tasks. For existing tasks, the setting is disabled to maintain compatibility with downstream processes that expect the data as STRING.

Current mappings include:

• VARIANT on Snowflake
• JSON on Google BigQuery

Note:

• If you are using Data Movement gateway to access your data source, version 2024.11.70 or later is required
• Supported with a SaaS application Preview connectors only

Replication tasks: JSON column mapping
Lake landing tasks: JSON column mapping