What’s New in Qlik Cloud

– October 2026 Updates –

Welcome to the next edition of the ‘What’s New in Qlik Cloud’ blog for October 2026, covering the features released in September 2026.

Authors: Roger Gray, BI Manager & Tom Cotterill, BI Consultant at Climber.

Data Analytics

It’s a packed month. Qlik Answers gains Fast and Thinking modes for assistants, image indexing in PDFs, and a new Semantic understanding tab for refining how your data model is interpreted. Your AI assistant can now build scheduled and triggered automations for you. Several preview features arrive, including Pages, new application themes, and a next-generation script editor with dark mode, along with a self-service feature preview capability to switch them on. On the orchestration side, a Visual Task Chain Viewer is introduced and the popular ‘when data is refreshed’ trigger returns, while validation rules gain date and time expressions. Direct Access gateway administrators get AWS PrivateLink support and containerised deployment.

Agentic AI

1. Choose between Fast and Thinking modes with assistants in Qlik Answers

Following the introduction of Fast mode for application analysis in July, the same choice now extends to Qlik Answers assistants. Fast mode gives quick responses to straightforward questions. Thinking mode provides deeper analysis for complex queries that need multi-step reasoning. You can switch between the two at any point in a conversation, adjusting the depth of analysis to suit the question in front of you.

2. Qlik Answers: index images in PDF documents

Knowledge bases using Qlik Answers enhanced accuracy can now index images within PDF files for semantic search. Images are processed alongside text using multimodal embeddings. This means answers can draw on visual content such as charts, diagrams, and infographics as well as the written text.

Images are indexed after the next reindexing operation
Currently available in US East (Northern Virginia) and Asia Pacific (Tokyo)

3. New business logic AI optimisation and semantic understanding for Qlik Answers

The business logic experience in AI optimisation has been revised to give a more focused way of preparing applications for Qlik Answers. A new Semantic understanding tab lets you review and refine the AI-generated descriptions of fields and master items. This gives you fine-grained control over how Qlik Answers interprets your data model.

4. Build scheduled and triggered automations from your AI assistant

Your AI assistant can now build automations that run on their own, not just ones you start by hand. Using the Qlik automation builder skill with the Qlik MCP server, you describe when an automation should run, for example “every weekday at 7am”. The assistant then creates it with the schedule already in place. You can also ask for an automation that another tool should start, such as a Qlik Answers assistant, a sheet button, or an AI agent. The assistant then sets it up to accept the values that the caller sends, such as an app ID.

Go from a plain-language request to a scheduled automation without opening the Automate editor
Build automations that agents and other tools can call, passing in values for the automation to work with
Check the schedule before the first run, as the assistant restates it in plain language alongside the technical rule
Connections used by an automation must already exist: the assistant can find and bind them, but cannot create them
An automation can have only one schedule

User Experience

5. Qlik feature preview

A new self-service capability lets you preview and enable upcoming features yourself, with no waiting. Look for the feature preview section in your user profile settings to get started.

Try new capabilities before they are generally available
Enable or disable preview features whenever you like
Give feedback directly on the features you test
Tenant administrators control which users have access, keeping rollout managed at organisation level

6. Build landing experiences with Pages (public preview)

Pages lets you build a free-form, canvas-based landing experience rather than being limited to horizontal swim lanes of collections, whether for yourself or for a group of users.

Build on an open canvas layout instead of fixed swim lanes
Mix widgets such as charts, rich text, and lists based on collections
Create multiple pages, tenant-wide, for a specific group, or for personal use

This is a public preview only. It is not generally available and may change based on feedback, which can be given via the feedback mechanism in the feature preview modal.

7. New application themes and visualisation settings (public preview)

Applications now include two new themes: Foundation, the new default, and New Horizon, which applies Qlik brand colours. Visualisation defaults have also been updated across combo charts, line charts, pie charts, filter panes, gauges, and KPIs.

This is a public preview and is subject to change.

8. Find the analytics you need, even when you can’t remember the name

Global search continues to evolve. As covered in our last edition, it can find content inside your analytics applications, starting with sheets and bookmarks. A partial term, a concept, or a term in another language can still surface the right application. This month it also returns results from the terms and categories in your business glossaries.

Searching visualisations and master items is still coming soon.

9. Scatter plot heatmap colour options

You can now set the start and end colours of the scatter plot heatmap, which makes it easier to match the chart to the styling of your app. The scatter plot switches to a heatmap once the number of data points passes a certain threshold, with intensity reflecting how closely the points cluster.

10. Smoother straight table bookmarks

Bookmarks on straight tables no longer need recreating when the table layout changes. Columns added after a bookmark was saved are now fully accessible under the chart exploration options.

Data Quality

11. Date expressions in validation rules

Validation rule expressions can now use date, time, and timestamp functions directly from the rule builder. This extends the arithmetic and string/number syntax already available. Inline validation gives actionable error feedback before a rule is saved.

Interpretation: Date#, Time#, and Timestamp# parse text values as dates, times, or timestamps
Formatting: Date, Time, and Timestamp display values as text in your chosen format
Current date and time: Today() and Now()
Date arithmetic: AddMonths(date, n [, mode]) and AddYears(date, n), plus the “-” operator for the duration between two dates, times, or timestamps
Component extraction: Year, Month, Day, and Week (ISO week number)

Developer tooling and performance

12. Try before you commit: temporary compute engine overrides in performance evaluation

Application performance evaluation now lets you test a larger engine from the evaluation screen. Pick any engine size larger than the one assigned (Large 40 up to Large 200) and run it once. The override applies to that single run and then reverts automatically, with no new permissions, no cost, and no commitment.

Every engine size is visible to every user, so no Large application capacity licence is needed to try one
It’s a quick way to judge whether a bigger engine is worth making permanent, and it stacks with existing recommendations for a bigger jump
In one example, moving an app from Large-60 to Large-120 cut initial load time by 38%, though results will vary by application

13. Data load editor and Script editor: IDE-grade editing experience with dark mode (public preview)

The Data load editor and Script editor now offer an IDE-grade experience for writing Qlik script. Activate it from your user profile under Feature preview and switch back to the classic editor at any time from the Next-gen editor menu in the toolbar.

Dark mode: for the script editor area (other parts of the interface are unaffected)
Improved syntax highlighting: better contrast and readability
Code folding: collapse LOAD statements, subroutines, FOR loops, and other blocks
Code navigation: Go to Definition, Go to References, Peek, and a minimap
Syntax hints on hover: inline help and links to the help portal
Autocomplete: keywords, functions, variables, and table names, in a resizable popover
Command Palette: multi-cursor selection, indenting, fold/unfold all, and word wrap
Code refactoring: Rename Symbol across the entire script

Several keyboard shortcuts have been added or updated as part of this experience.

This is a public preview and is subject to change.

14. Application script lifecycle tools for the Qlik MCP server

New Qlik MCP tools support the full application and script lifecycle from your LLM client, for both guided authoring and automated workflows. They let you:

Create applications and generate or retrieve script content
Retrieve, replace, and patch the application load script
Trigger, monitor, and cancel reloads, and retrieve reload logs
Inspect the resulting application data model

15. Visual Task Chain Viewer

Task dependencies can now be seen visually, rather than having to map out how scheduled tasks connect in your head. This first phase adds a tree-view chain visualisation built for the most common pattern, sequential dependent tasks, such as a data pipeline step chained to an app reload, shown as a simple parent-child structure.

See sequential task chains laid out visually
View dependency relationships clearly
Spot where a chain is running or has failed, directly in the view

Coming next: a future phase will add graph-based views supporting multiple upstream and downstream dependencies for more complex orchestration.

16. ‘When data is refreshed’ event is back

When enhanced self-service scheduling arrived in April 2025, the option to trigger a reload schedule when a dependent dataset was updated was removed. It’s now returning, built natively into the task-based scheduler and compatible with its multi-task model. In the task editor, under Based on > Event, select When data is refreshed to trigger a task automatically when an update is detected in an upstream Qlik Talend Data Integration project that loads data into an analytics application.

17. OAuth Client ID Metadata Documents (CIMD)

Tenant administrators can now configure an MCP connection between their AI platforms and Qlik Cloud tenants using OAuth Client ID Metadata Documents. CIMD reduces the manual steps needed to configure OAuth clients and removes the need to manage client secrets by hand.

18. Settings reorganised in the Administration activity centre

The Settings page in the Administration activity centre has been reorganised to make individual settings easier to find.

19. AWS PrivateLink support for Direct Access gateway

Customers with Qlik Cloud Analytics Enterprise subscriptions or Qlik Sense Enterprise SaaS can now establish an AWS PrivateLink endpoint between their data and their Qlik Cloud tenant using the Direct Access gateway. Data loaded into Qlik Analytics applications then travels over a private network connection. This capability was introduced on 22 September 2026.

20. New Direct Access gateway version (1.8.0)

Version 1.8.0 brings new features and fixes, including the PrivateLink support above:

Containerised deployment (with Linux support): alongside the existing Windows installation, the gateway can now run in a Docker container on Linux and Windows. This first container release supports the ODBC connector (PostgreSQL, SQL Server, and Oracle) and the REST connector.
Automatic registration from the command line: register the gateway without the Administration activity centre, which suits multi-tenant deployments and unattended scenarios, on both Windows and containerised installs.
File connector improvements: a configurable timeout (FILE_REQUESTDOWNLOAD_ACK_TIMEOUT_SECONDS) for the initial download acknowledgement, to help mitigate DirectAccess-2007 errors on File connector reloads, plus diagnostic logging for download stalls.
Silent install and uninstall: these now report the true outcome rather than success when post-installation steps fail, and prerequisite installers run silently.
Connector startup script hardening: the scripts now explicitly enable Windows Command Extensions, preventing probing of an untrusted path and silent failure of configuration overrides.
Driver and security updates: the Google BigQuery ODBC driver is now 3.3.1.3003, and all ODBC drivers except Apache Spark now use OpenSSL 3.5.7 and libcurl 8.21.0.

Data Integration

As we move into October, we’re looking back at the latest Qlik Data Integration updates, with improvements across data quality, stewardship, API governance, large-file handling, and declarative pipeline development.

We’ve also included one useful MCP enhancement from the previous release that we missed last time. There is a good mix this month, ranging from practical improvements to existing capabilities through to further developments in AI-assisted pipeline creation.

1. Improved support for large QVD and Parquet files

Qlik has extended its catalogue and data quality capabilities to handle considerably larger QVD and Parquet files stored in cloud storage. Files larger than 1 GB can now be registered in the Qlik Cloud Catalog, removing the previous size barrier for organisations working with larger datasets. For profiling, the existing size-based rules still apply, so datasets exceeding 12 million rows receive light profiling rather than a full profile.

The improvement also extends to data quality. Qlik can now calculate quality scores and Qlik Trust Score™ for files larger than 1 GB and up to 100 GB, whether those files are registered directly in the catalogue or included within a data product.

That means data product owners and consumers can see quality and trust information across larger datasets alongside everything else. Governance teams get a more complete view of quality across the catalogue. It is a useful pairing of updates, extending Qlik’s catalogue and governance capabilities to datasets that previously fell outside the supported file-size range.

More information:

Managing field-level metadata and data profiling
Data quality for connection-based datasets
Data quality for uploaded files

2. Data contracts gain volume expectations

Qlik’s data contracts can now include volume expectations, allowing teams to compare the record count of a dataset against a static baseline that they define. Building on the existing data quality expectations framework, the feature addresses another important question: is the expected volume of data arriving?

That can be useful for spotting issues that might otherwise slip through unnoticed. A dataset may still look structurally valid, but if its normal daily volume suddenly drops from hundreds of thousands of rows to only a fraction of that, something has probably gone wrong upstream.

By adding volume expectations to the contract, Qlik can make that kind of deviation visible as part of the same governed framework used for other dataset expectations. A small addition, but a useful one for teams looking to define more comprehensive expectations around the datasets they depend on.

3. Data Stewardship gets more collaborative

Qlik has introduced two useful improvements to Data Stewardship sprints, both aimed at making the remediation process easier to coordinate.

The first is in-cell commenting. Data stewards and sprint owners can now add comments directly to individual cells while working through data issues. That means questions, explanations, and additional context can stay attached to the exact value being discussed, rather than disappearing into a separate email, chat thread, or meeting.

Other domain experts can reply to the same comment thread, and the discussion remains with the cell even when people are working at different times. For issues that need input from several people before a decision can be made, that should make the reasoning behind a correction much easier to follow.

Qlik has also added automatic notifications for stewardship sprint assignments. Data stewards are now notified when they are added to or removed from a sprint, or when records are assigned to them. Previously, sprint owners had to communicate those changes themselves. Automating the notification removes a small but potentially troublesome manual step and helps ensure that stewards know when work is waiting for them.

Together, the two updates make stewardship sprints feel more like a collaborative workflow and reduce some of the manual coordination involved in managing remediation activity.

For details, see Working with cell comments in a resolution sprint and Sprint notifications.

4. API contracts get stronger governance

Qlik has expanded API Contracts with new capabilities for teams that design, share, and publish APIs. Teams can now share entire API repositories, rather than individual versions, generate contracts directly from a prompt, and publish those contracts into the Qlik Cloud Catalog. Once published, the contract becomes immutable and versioned, creating a stable reference point for anyone building against it.

That brings a few useful governance benefits. Developers can work against a fixed contract that will not unexpectedly change beneath them. Implementation issues can be traced back to the exact contract version involved. It also opens the documentation up to a wider audience, allowing architects, consultants, and analysts to review contracts and submit change requests without needing to be the people writing the API itself.

For organisations trying to treat APIs as governed, reusable assets rather than loose technical documentation, this is a useful step forward. Qlik notes that the capability is not supported in Qlik Cloud Government or Qlik Cloud Government – DoD.

More details: Working with multiple versions

5. Date expressions come to validation rules

Qlik has expanded validation rule expressions to support date, time, and timestamp functions. This brings temporal checks into the same rule-building framework already used for arithmetic, string, and numeric conditions.

That includes functions for parsing and formatting dates, times, and timestamps, as well as retrieving the current date or timestamp. Rules can also perform date arithmetic, calculate durations between values, and extract components such as year, month, day, and ISO week number.

The practical benefit is that validation rules can now test more than just whether a value is present or correctly formatted. Teams can start checking whether dates make sense in context, for example whether an expiry date is in the past, whether an order date falls within an expected period, or whether two timestamps are separated by an acceptable interval.

Qlik has also added inline expression validation, giving users actionable feedback on errors before a rule is saved. A compact update that makes validation rules far more useful for time-sensitive datasets.

More information: Working with validation rules

6. MCP tools for declarative pipelines

Qlik has added three new MCP tools specifically for declarative pipeline development, helping coding agents such as Claude Code and GitHub Copilot work against a live Qlik Cloud tenant rather than relying purely on assumptions.

The new tools allow those agents to search for pipeline projects and connections, inspect a project’s binding values, and discover the source tables and views available through a data connection.

That matters because declarative pipeline development is only as reliable as the information the coding agent has available. If it guesses the wrong connection name, table structure, or project binding, the pipeline can fail when it is imported. These MCP tools let the agent interrogate the tenant first and generate its output with much better awareness of the actual environment.

In practical terms, this should make AI-assisted pipeline development less speculative and more grounded in the real configuration of the Qlik tenant. A useful addition, and one that was worth picking up after we missed it in the previous edition.

Summary

Data Analytics

September 2026 was one of the busiest months of the year, with Qlik Answers once again at the centre. Assistants gain Fast and Thinking modes, knowledge bases can now draw on images inside PDFs, and the new Semantic understanding tab gives developers finer control over how data models are interpreted. AI assistants can now build scheduled and triggered automations, and the Qlik MCP server gains tools for the full application and script lifecycle. Business users get a first look at Pages and the new themes through the self-service feature preview, alongside practical improvements to scatter heatmaps and straight table bookmarks, and data stewards benefit from date and time functions in validation rule expressions.

Developers gain a next-generation script editor with dark mode, and temporary engine overrides to test performance. On the orchestration side, the visual task chain viewer and the returning ‘when data is refreshed’ trigger make scheduling easier to understand and automate. Direct Access gateway 1.8.0 adds containerised deployment and PrivateLink support. Several of this month’s headline features are public previews, so test them in a non-production context first and expect changes.

Data Integration

Overall, also a varied set of practical improvements across several areas of the Qlik Data Integration platform. This latest set of updates continues Qlik’s focus on improving governance, data quality, and the developer experience across the Data Integration platform. Support for larger QVD and Parquet files extends catalogue and quality capabilities to more substantial datasets. Volume expectations give data contracts another useful way of identifying potential issues before they reach consumers.

The Data Stewardship improvements make remediation more collaborative and easier to coordinate. The changes to API contracts and validation rules continue to strengthen governance across the platform. Finally, the new MCP tools add further context to AI-assisted declarative pipeline development by allowing coding agents to work with information taken directly from the Qlik Cloud environment.

Thanks for reading the Qlik Cloud monthly update.
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WANT TO KNOW MORE? CONTACT US!

Have a question about one of this month’s updates or how it could benefit your organisation? We’d be happy to help.

Bas Haarhuis

Advisor Data & Strategy
bas.haarhuis@climber.nl
+31 6 39 46 39 65

Jordy Wegman

BI Manager
jordy.wegman@climber.nl
+31 6 11 62 68 58

Gepubliceerd 2026-10-13

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