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- Qlik Cloud August 2025: what’s new
Reading time: 10 min 
In this video, we cover the latest Qlik updates, including new features in Qlik Cloud Analytics, governance enhancements, app performance tools, and GenAI connectors. These updates are designed to help Qlik users unlock more value from their data with improved usability, governance, and performance.
Qlik Cloud Analytics introduces Table Recipe, a lightweight, spreadsheet-like experience for preparing single-table datasets. This interactive playground is designed to make quick, no-code data manipulations accessible to everyone, while providing instant visual feedback. Every table recipe is a sequence of steps, giving you a structured and repeatable way to apply operations on your data.
Key highlights:
With Table Recipe, Qlik Cloud now combines spreadsheet-like simplicity with platform-level governance, extending the reach of self-service data preparation for analytics and AI.
Loading and preparing data with Table recipe
One of the most requested governance features has arrived! Qlik Cloud now gives administrators full control over who can create, manage, or only read data connections. This new security scope delivers enterprise-grade governance that goes beyond spaces, ensuring consistent enforcement across your entire tenant.
Highlights include:
This long-awaited enhancement strengthens data governance, security, privacy, and compliance while giving organizations the precision they’ve been asking for.
Managing data connections for administrators
New GenAI connectors have been added for:
Amazon Bedrock – Converse API analytics source
Google AI – Gemini analytics source
The OpenAI Connector now supports “GPT 5, GPT 5 mini and GPT5 nano” models.
Experience a smarter way to learn. Qlik’s new Learn page (replacing Getting started) offers step-by-step, outcome-based learning paths to help you succeed.
From onboarding to advancing your skills, every step is designed for real results. Track your achievements, dive into fresh content, and gain the most from Qlik—all in one place.
Accessing the Administration activity center
The syntax, functionality, and documentation of window functions have been enhanced to improve usability and flexibility. Window functions are commonly used for analytics and ML data preparation scenarios that require aggregations across different partitions without losing the grain of the input data.
Enhancements include:
We are happy to announce improvements to our Qlik Talend Cloud Pipelines monitoring API endpoints.
[UPDATED] GET/v1/di-projects/{projectId}/di-tasks/{dataTaskId}/runtime/state
With this new API release, we’re bringing enhancements to the existing ‘Get project task runtime state’ API.
It is now enriched with many new fields that will be helpful for your task monitoring in real-time, such as the run state, start/end time and duration, but also the task dataset count (incl. datasets in error), the gatewayID, name and getawayTaskName, or the latency for continuous tasks among other fields.
[NEW] GET/v1/di-projects/{projectId}/di-tasks/{dataTaskId}/runtime/state/datasets
In addition to improving the runtime state API, we’re launching a new “list runtime dataset states”, which will give you dataset-level details related to your tasks (eg. dataset name and ID, dataset state, processing start and end time and even the processed record count when applicable).
These APIs are available in production today.
The ‘Get project task runtime state’ API enhancements are already available in Qlik Automate. The new ‘dataset state’ API will be added in Qlik Automate soon.
REST API: Data integration projects
A new Number of retries before returning a table error setting has been added to the table error handling settings for replication and landing tasks. Previously, when a table error occurred, the table would be suspended or the task would be stopped (according to the selected error handling action). This sometimes resulted in tables being suspended during the SaaS application maintenance window. With this new option, it is now possible to determine how many times the table should be retried before the table error handling policy is triggered. This option is especially useful if your SaaS application undergoes periodic maintenance, as you can override the default number of retries (3) so that the maintenance can be completed without triggering the table error handling policy.
A new Map compatible source JSON columns to JSON columns on the target option has been added to the task settings’ Metadata tab. With new tasks, this option is selected by default if there are compatible source JSON data types which are also supported by the target. However, before this option was introduced, JSON columns were mapped to STRING on the target. Consequently, for existing tasks, this option will be disabled by default as any downstream processes – such as transformations – will expect the target data to be in STRING format. You can either leave the option disabled or you can edit the downstream processes to be compatible with JSON format and then enable this option.
When previewing an SQL transformation, the results will now include the column data types.
If you are using Data Movement gateway to access your data source, this feature requires version 2024.11.70 or later.
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