Qlik Cloud July 2026: what’s new

August 5, 2026

Reading time: 20 min

ANALYTICS

Date picker input type for write table editable columns

Write table now supports a Date picker input type for editable columns. Users can select dates directly in table cells and save changes to the change store, alongside existing manual entry and single-selection input methods.

For more information, see Date picker.

Export Qlik Answers conversations as PDFs

You can now export new conversations with the Qlik Answers assistant as PDF files. This capability supports conversations involving both structured and unstructured data within an application and assistant context. Note: conversations created before this release cannot be exported.

Business glossary context for Qlik Answers application analysis

Qlik Answers now uses linked business glossary definitions and synonyms when indexing application master items, improving semantic matching and consistency across terminology used in user questions.

Glossary definitions are evaluated at indexing time. If glossary definitions are updated after indexing, reindex the application to apply the changes. Only glossary terms in Verified state are considered.

Working with applications in Qlik Answers

Combining master item descriptions and business glossary terms

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

Fast Mode for Qlik Answers

Qlik Answers now includes Fast mode — a new default experience for application analysis that returns answers in seconds.

What changed

When you open an application in Qlik Answers and ask a question, you are now in Fast mode by default. Fast mode is optimized for direct, retrieval-style questions against structured data: pulling a number, slicing by a dimension, generating a quick chart. For these kinds of questions, it is significantly faster than before.

This is the mode you will use most of the time. It handles the everyday questions well, and it handles them fast.

What stays the same

Thinking mode is still there, still works exactly as before, and is still the right choice for complex analysis, multi-step reasoning, or building charts and sheets from scratch. Nothing about Thinking mode has changed — it is just no longer the only option.

Switching modes

If Fast mode is not what you need, switching takes one click. The mode toggle sits in the chat interface once you have selected an application. Your conversation context carries over when you switch — you do not lose what you were working on.

If Fast mode genuinely cannot answer a question, it will tell you so rather than returning a weak response. A Think more button appears below the answer, and clicking it reruns your question in Thinking mode with full context preserved. You do not need to re-ask anything.

When to use each

Use Fast mode for questions like:

• “What were total sales last quarter?”
• “Show me revenue by region for Q1 2026”
• “Which sales rep had the highest bookings in May?”
• “Bar chart of top 10 customers by order value”

Switch to Thinking mode when you want to:

• Create or modify sheets and dashboards
• Ask questions that span both structured data and documents or knowledge bases
• Do multi-step or comparative analysis
• Dig into something where the answer is not straightforward

Availability

Fast mode is on by default for all users with access to application analysis in Qlik Answers. No configuration required.

Application analysis

Answering questions with Qlik Answers

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

Table Recipe: Data quality with semantic types

Table Recipe now has native data quality capabilities to detect, visualize, and fix invalid or inconsistent data. These capabilities make it easier to prepare clean, reliable datasets for analytics or machine learning, without leaving the no-code, spreadsheet-like interface.

• Data type and semantic type discovery: Each column is automatically assigned a data type based on the data it contains. Data types include native data types such as integer, date, and text, as well as semantic types: predefined (email, phone number, postal code, country code, and more) or custom (dictionary-based, pattern-based, or compound). You can manually change the assigned type at any time from the column menu.
• Column quality bar: Each column header displays a quality bar showing the proportion of valid (green), empty or null (black), and invalid (red) values.
• Cell-level invalid value indicators: Cells containing invalid values are flagged in red.
• Validity-based filtering: Click any segment of a column’s quality bar to instantly filter rows by quality status (valid, invalid, or empty or null). Filters can also be applied from the column menu or the filter dialog.
• Cleanse and contextual remediation suggestions: The Cleanse function lets you replace invalid, null, or empty values in a column. Table Recipe also surfaces relevant remediation suggestions, such as replace, clear or fill, based on detected invalid values, as well as conversion function suggestions based on the detected type.

Data quality features are available in both standalone table recipes and the table recipe processor in a data flow, and requires the data quality license entitlement (Qlik Cloud Analytics Premium and Enterprise, and Qlik Sense Enterprise SaaS).

Assessing the quality of the data

Table Recipe: Calculated column and Format number functions

Table Recipe adds calculated columns and number formatting, bringing more flexible data preparation logic into the no-code, spreadsheet-like interface.

• Calculated column: Add a new column based on a Qlik script expression combining existing columns and functions. This lets you build more complex logic in a single recipe step, covering use cases that previously required scripting, with a built-in expression editor providing syntax highlighting, autocomplete, inline function guidance, and direct links to Qlik Help.Columns functions
• Format number: Change how numeric values are displayed using predefined or custom patterns, with configurable decimal and thousand separators. The Format number function is also added to the Numbers processor in Data Flow.Numbers functions
• When configuring a filter, a “Show more” button lets you load more value suggestions from the selected column.

DATA INTEGRATION

Introducing change management for lake landing replication tasks

Store changes settings are now available for lake landing replication tasks in a dedicated Store changes tab. With these new capabilities, lake landing replication functionality further bridges the gap with standard replication functionality, enabling consistent change management across replication task types.

Key features include:

• Change Table capture: Automatically store INSERT, UPDATE, and DELETE operations from the source in Change Tables on the target platform for incremental downstream processing.
• DDL handling options: Choose whether to automatically apply schema changes from the source to Change Tables or ignore DDL modifications to maintain fixed table structures.
• Configurable storage: Select whether to capture both before and after image data on updates, and customize Change Table naming conventions with configurable suffixes and header column prefixes.
• Header column management: Exclude specific system metadata columns from Change Tables to reduce storage requirements, or keep all header columns for complete audit information.
• Flexible full load behavior: Determine how existing Change Tables are handled when a full load starts—DROP and CREATE, delete old changes only, or keep all historical changes.
• Reorganized settings: Change Data Partitioning settings have moved from the General tab to the new Store changes tab for better organization and usability.

Store changes settings

Qlik Trust Score™ forensic for Data products

Data products Qlik Trust Score™ drill down now gives you a deeper, more actionable view of trust and quality.

What’s new

A new Quality tab inside each data product gives you forensic-level visibility into your composite Qlik Trust Score™, so you can see not just where the score sits today, but what’s moving it and which datasets are driving the change.

From the Quality tab you can follow the score from headline number all the way to root cause, layer by layer.

Why this matters

Data product owners can now pinpoint exactly what’s impacting their trust score and why, getting to root cause in just a few clicks without leaving the data product. That transparency enables the Qlik Trust Score™ to be a truly explainable signal consumers can rely on, and producers can act on.

Qlik Trust Score™

Advanced expressions and conditional branching in validation rules

You can now define advanced data quality checks with expressions using Qlik script syntax, directly from the rule builder. Rules also now support multiple conditions with else if for branching logic, all without leaving the guided user interface.

What’s available

• Arithmetic operands: Use +, -, *, /, and modulo between field references and literals on either side of a validation operator. For example: fieldA + fieldB = fieldC, fieldX – 100 > 0.
• Typed function operands (string and number functions): Reference functions including Len, Trim, Left, Right, Mid, IsText, IsNum, Floor as operands in any rule condition.
• Parenthesised sub expressions: Control evaluation order with parentheses. For example: (fieldA + fieldB) * 0.8 = fieldC.

Users also benefit from inline expression validation with actionable error feedback before the rule is saved.

Working with validation rules

Request access to data products

Data consumers can now request access to data products directly from the data product marketplace when they lack the necessary permissions to access a dataset.

Previously, users who discovered a data product of interest but did not have the required connections or permissions — such as the ability to read a Snowflake table — had to manually identify the appropriate person in their organization to request access, causing delays and interruptions to their workflows.

With this new feature, users can submit an access request directly through the marketplace by completing a form that captures key details, including their name, job position, reason for the request, and the level of permission required. This enables organizations to streamline and customize their data access workflows, reducing the time data consumers spend waiting for access and improving overall productivity and data utilization.

Requesting access to spaces

Enriched and automated classification through semantic types

Qlik Cloud can now automatically detect and flag sensitive data based on semantic types, replacing purely manual sensitivity declaration. Classifications are then constantly applied across datasets, and fields not covered by a semantic type can still be classified manually. Users can also apply regulations directly at the dataset level when it applies. This information will surface automatically when activating a data product, ensuring consumers are aware of compliance requirements before a data product is visible on the marketplace for consumption.

Managing semantic types

Improved header column support for Open Lakehouse streaming tasks

Header columns are metadata columns (such as timestamp) that Open Lakehouse adds to every ingested record. We have introduced the following set of improvements to give more control over header column management:

• Header column visibility is now configurable across streaming landing and streaming transform tasks.
• In streaming transform tasks, a toggle controls whether header columns are hidden, shown for the current view, or shown for the history view.
• The expression builder now surfaces landing headers making it easier to use in expressions.
• A new setting also lets you expose the hdr__from_timestamp in the current view, enabling partition-based queries when partitioning by event ingestion date.

Showing header columns in views

Standard view headers

Note: Not supported in Qlik Cloud Government.

Design, document, and test APIs in Qlik Cloud

API Designer is now available in Qlik Cloud, covering three key stages of the API development lifecycle: design, documentation, and testing. With an easy learning curve, users without API coding experience can design APIs and publish their documentation directly in Qlik Cloud.

The graphical interface lets you create OpenAPI Specification (OAS)/Swagger or RAML API definitions without learning the underlying syntax. Repository-based sharing supports team collaboration on API projects. Completed APIs can be implemented in Talend Studio and deployed.

Designing API contracts

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

Full Stitch SaaS connectors catalog now available

The full Stitch SaaS connectors catalog is now natively integrated into Qlik Talend Cloud, giving you access to over 100 pre-built connectors for popular sources including Salesforce, Jira, Marketo, Zendesk, and more. SaaS application connectors now support Replication, Data pipeline, and Open Lakehouse use cases. While most SaaS application connectors are fully certified, some of them are classified as Lite, meaning they have been tested against a limited set of use cases.

For a list of supported connectors, see Supported SaaS applications. The list will constantly grow as more connectors become available.

Note: Not supported in Qlik Cloud Government. Customers using Data Movement gateway who want to create new tasks with SaaS application connectors must upgrade to Data Movement 2025.11.66 or later.

……. … ………… ….

• Qlik Cloud June 2026: what’s new – read here.
• Qlik Cloud May 2026: what’s new – read here.
• Qlik Cloud April 2026: what’s new – read here.
• Qlik Cloud March 2026: what’s new – read here.
• Qlik Cloud February 2026: what’s new – read here.
• Qlik Cloud January 2026: what’s new – read here.

Any questions please contact our consultants. Responding in one working day.

What's New in Qlik Cloud