What’s New in Qlik Cloud

– March 2025 Updates –

Welcome to the next edition of the ‘What’s New in Qlik Cloud’ blog for March 2025!

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

Data Analytics

Qlik Cloud continues to evolve with new features and improvements designed to enhance analytics, automation, and user experience. This month brings a host of updates, including expanded user attributes, enhanced security and access control, new connectors, and powerful analysis tools. Let’s dive into the details of what’s new!

1. Improved Navigation Menu Customisation

Based on customer feedback, Qlik has refined the custom navigation menu to offer better usability and flexibility:

Hover menu is off by default to prevent accidental menu activation.
Sheet title expressions are now applied when available, improving dynamic labelling.
Drawer panel can be placed on the right for more layout options.
Separate items mode includes new spacing, border, shadow, and divider configurations.
Padding and margin updates for a cleaner interface.
Icons and group symbols now match the label colour for improved readability.

These improvements enhance the overall user experience, making navigation more intuitive and adaptable.

2. New Relative Importance Analysis for Advanced Insights

Relative importance analysis is now available in the Analyses feature, helping users quickly determine which dimension values contribute the most to an overall total. This is particularly useful for:

Pareto analysis (80/20 rule): Identify the top contributors that drive the majority of the results.
Proportion-based insights: Understand the share of each category in a dataset.

With this tool, businesses can better prioritise their efforts based on data-driven insights.

3. Sheets & Bookmarks Now Accessible in App Toolbar

By popular demand, Sheets and Bookmarks have been restored to the default app toolbar configuration. This allows users to:

Quickly switch between sheets.
Easily manage bookmarks for frequently used views.
Configure toolbar settings via UI preferences.

This small but impactful update improves workflow efficiency and accessibility.

4. New Direct Access Gateway Version

The latest Direct Access Gateway update (v1.7.1) introduces multiple enhancements, including:

New REST Connector: Securely access private REST API endpoints via Direct Access Gateway, enabling seamless data streaming into Qlik Sense. This is a significant enhancement enabling secure access to REST API data that is behind a firewall.
Customisable Cache Directory: Override the default disk location for caching data chunks to optimise system performance.
Increased ODBC Table Retrieval Limit: Adjust the number of tables retrieved (default: 10,000) to accommodate large databases.
Google BigQuery Multi-Catalog Support: Now access multiple Google BigQuery projects within a single connection.
Databricks Unity Catalog Support: Fetch data from Unity Catalog within Databricks for enhanced data governance.
ODBC Data Error Mitigation: Override problematic data types when vendor ODBC drivers introduce errors.
Improved Logging: Connector start, exit, and restart logs are now consolidated in the (DirectAccessAgent) log file for better troubleshooting.

These updates improve connectivity, scalability, and performance, making data integration more seamless than ever.

5. Qlik Answers Connector for Qlik Application Automation

Qlik is rolling out the Qlik Answers connector, a powerful new addition to Qlik Application Automation. This connector enables users to:

Index new data on the fly, making it available for insights and automation in real-time.
Enhance action-oriented workflows by integrating unstructured data into decision-making processes.

With this new connector, businesses can leverage Qlik Answers to streamline knowledge management and improve efficiency.

6. Qlik Answers Assistants Now Supports Download Review Feedback

Qlik Answers now allows users to download review feedback as a CSV file. This makes it easier to track suggestions, implement improvements, and maintain documentation for team collaboration.

7. Qlik Answers Now Supports Google Drive & OneDrive

Qlik Answers knowledge bases can now connect directly to Google Drive and OneDrive, enabling organisations to use cloud-based documents as data sources.

8. Custom Group Support for Section Access in Qlik Cloud Analytics

Qlik Cloud Analytics now supports custom groups in Section Access, adding a new layer of flexibility for access control for organisations that wish to use Qlik Cloud’s user authentication. Organisations can now configure Section Access using:

IdP Groups: Groups managed by an Identity Provider (e.g., Okta, Azure AD).
Custom Groups: User-defined groups within Qlik Cloud.
Both IdP and Custom Groups: A combination of both for more granular access management.

By default, Section Access still relies on IdP groups, maintaining a familiar setup. However, this enhancement provides greater control over user permissions and security in analytics environments, making it easier to align access with business needs.

9. Enhanced Localisation with New GetUserAttr Attributes

For organisations looking to provide consistent localisation and language experiences between Qlik Cloud interfaces and their own applications, Qlik has added two new attributes to the GetUserAttr function. These attributes are pulled from the user’s profile settings on the tenant:

userLocale: Identifies the preferred language setting of the user, such as en for English or fr for French.
userZoneinfo: Retrieves the user’s time zone, for example, Europe/London or America/New_York.

With these new attributes, developers and administrators can better customise dashboards and applications to match user preferences, ensuring a seamless experience across different languages and time zones.

10. Updates to Scripting Documentation

Qlik has enhanced its scripting documentation to provide better guidance on key functions:

Colour Functions: Expanded examples and use cases.
Null Functions: Detailed explanations and improved clarity on handling null values.

These updates ensure developers have the information they need to write more effective scripts.

Data Integration

The latest enhancements in Qlik Talend Cloud introduce key improvements in database failover certification, performance, data type support, and platform compatibility. These updates require Qlik Data Gateway – Data Movement 2024.11.14 or later. For upgrade instructions and resolved issues, refer to the Upgrading the Data Movement Gateway installation documentation.

1. PostgreSQL Failover Certification

Qlik now officially supports working with a secondary database after failover for the following PostgreSQL-based data sources when accessed via the PostgreSQL source connector:

Google Cloud SQL for PostgreSQL
Amazon RDS for PostgreSQL
On-premises PostgreSQL

For setup guidance, see Setting up failover.

2. MySQL Performance Optimisation

Previously, when using a MySQL-based source with limited LOB size, Data Movement Gateway retrieved LOB columns via source lookup. Now, these columns are read directly from the MySQL binlog, significantly improving performance.
Note: This change does not apply to the JSON data type.

3. Data Type Mapping Updates

Changes have been made to LOB column mappings for Amazon Redshift and Snowflake targets:

Amazon Redshift Target

BLOB Maps to VARBYTE(16777216)
NCLOB Maps to NVARCHAR(65535)
CLOB Maps to NVARCHAR(65535)

Snowflake Target

BLOB Maps to BINARY(8388608)
NCLOB Maps to NVARCHAR(16777216)
CLOB Maps to VARCHAR(16777216)

4. Expanded Data Type Support

IBM DB2 for LUW Source: Now supports the BOOLEAN data type (available from DB2 for LUW 11.5).
Google BigQuery Target: Now supports the BIGNUMERIC data type.

DDL History Control Table – Expanded Target Support

Previously limited to Databricks and Microsoft Fabric, the DDL History control table is now available for additional targets:

Amazon Redshift
Amazon S3
Google Cloud Storage
Snowflake

For details, see DDL History.

5. Google Cloud SQL for PostgreSQL – Non-Superuser Support

You can now replicate from Google Cloud SQL for PostgreSQL using a non-superuser account, providing greater flexibility in database permissions.
For more information, see Using an account without the superuser role.

6. Certified Platforms & Driver Updates

Databricks Target: Now certified for 15.4 LTS.
Oracle Source & Target: Now certified for Oracle 23ai.
- Certified for Oracle Standard Edition only.
- Source support requires TDE encryption.
Databricks Driver Update: Simba Spark ODBC Driver 2.8.2 or later is now required for data movement to Databricks.
- Customers should update via the driver installation utility or manual installation.
- See Driver setup for more details.

7. End of Support Notices

The following database versions are no longer supported:

PostgreSQL 12.x
IBM DB2 for z/OS 2.4
Databricks 9.1

8. New Data Lakehouse Capabilities for Snowflake Projects

Qlik Talend Cloud pipelines now offer two powerful features to help build open lakehouses with Snowflake. These enhancements provide greater flexibility in data storage and processing and can be used independently or together.

9. Lake-Landing Ingestion for Snowflake Pipelines

The new lake-landing task enables low-latency replication of data to your preferred cloud storage, reducing the workload on Snowflake’s compute layer. By allowing Snowflake storage to consume data at a scheduled, slower pace, this feature helps minimise warehouse compute uptime and costs.

10. Support for Snowflake-Managed Iceberg Tables

Storage, Transform, and Data Mart tasks can now be configured to store data on external cloud storage (Amazon S3, Azure Data Lake Storage, or Google Cloud Storage) as Snowflake-managed Iceberg tables.

These tables are fully managed by Snowflake and provide an optimised way to store and query structured data.
They are compatible with the Snowflake Open Catalog (formerly Snowflake Polaris), ensuring seamless interoperability with any Iceberg-compatible engine.

With these new capabilities, Qlik Talend Cloud makes it easier than ever to integrate, store, and process data efficiently in a modern Data Lakehouse architecture using Snowflake.

For more information, please see Landing data to a lakehouse.

11. New Freshness Indicator for Real-Time Data Tracking

The latest update to Qlik Talend Cloud introduces a Freshness Indicator, allowing users to monitor data freshness in real-time based on the latest updates from their data sources. This feature helps immediately assess data timeliness and reliability.

How Freshness is Determined

For File-Based Data: The freshness reflects the last time the data was updated.
For Pipeline-Published Data: The freshness reflects the last time the dataset was updated by a pipeline.

Where to Find the Freshness Indicator

The Freshness Indicator is available in the Overview tab of a dataset, accessible through Qlik Cloud Data Catalog or Data Products Marketplace.

Freshness Calculation Based on Update Method

The time displayed in the Freshness Indicator depends on the method used to update the data:

Change Data Capture (CDC) Method
- Reflects the last event on the data source.
- Example: If the data source was updated at 9:00 AM, and the pipeline ran at 10:00 AM, when you check at 11:00 AM, the freshness will show “2 hours ago”.
Reload and Compare Method
- Reflects the last pipeline run.
- Example: If the data source was updated at 9:00 AM, and the pipeline ran at 10:00 AM, when you check at 11:00 AM, the freshness will show “1 hour ago”.

Additional Notes

Computing data profiles or quality checks does not affect the freshness timestamp.
The “Last Modified” column in the Catalog tab only reflects changes to the dataset itself (e.g., renaming or editing metadata), not actual data updates.
Qlik Talend Cloud Premium users: The data quality feature is not available in this subscription tier.

With this new Freshness Indicator, users can make faster, data-driven decisions by ensuring they are working with the most up-to-date datasets.

12. Introducing Qlik Trust Score™ – A New Standard for Measuring Dataset Trustworthiness

High-quality data starts with trust. Building on the foundation of Talend Trust Score™, Qlik Cloud now introduces the Qlik Trust Score™. It is a powerful tool designed to streamline data quality assessments and provide immediate visibility into the reliability of data assets across your organisation.

With a simple 0 to 5 numeric score, the Qlik Trust Score™ offers a clear, actionable measure of data trustworthiness, calculated based on multiple data quality dimensions. Organisations can customise the score by adjusting dimension weights to align with their specific data governance needs.

Key Benefits of Qlik Trust Score™

Customisable Scoring: Adjust weights and enable/disable dimensions to align with business-specific data quality goals.
Actionable Insights: Identify data gaps through key quality dimensions, including Validity, Completeness, Discoverability, and Usage.
Enhanced Transparency: Track dataset freshness and usage metrics, fostering collaboration and trust across teams.

Please note that this feature is available exclusively for Qlik Talend Cloud Enterprise users.

How Qlik Trust Score™ Works

The Qlik Trust Score™ provides a global quality indicator, aggregating several metrics into a single, easy-to-understand score. It helps answer the key question, “How trustable is my dataset?”.

You can find the Qlik Trust Score™ in the dataset overview, alongside additional insights such as:

The overall Qlik Trust Score™ and a percentage representing dataset health.
Breakdown of the factors influencing the score, grouped into four main quality dimensions:
- Validity: Assesses data integrity, including the presence of valid values and proper semantic types. Empty values are not considered valid.
- Completeness: Measures the proportion of empty records in the dataset.
- Discoverability: Evaluates how well-documented a dataset is, based on metadata quality (e.g., descriptions, tags) and whether it is referenced in activated data products.
- Usage: Indicates how frequently the dataset is used across dependencies, including Analytics apps, data flows, and preparations. Also considers view counts of these dependencies.

Data quality must be computed at least once to view a Qlik Trust Score™.

Configuring Qlik Trust Score™

Users can fine-tune the Qlik Trust Score™ calculation by adjusting dimension weights. This customisation applies globally across all datasets within the tenant.

How to Configure the Qlik Trust Score™:

Navigate to Qlik Talend Data Integration > Data Quality > Qlik Trust Score™.
Activate or deactivate specific dimensions using the toggle button.
Note: “Validity” and “Completeness” cannot be deactivated as they are core data quality indicators.
Adjust dimension weights using the plus/minus controls.
Note: All dimensions must sum to 100%.

Before configuring, ensure data quality features are supported for your dataset type (file-based or connection-based). For more details, refer to Data quality for connection-based datasets and Data quality for file-based datasets.

Summary

These updates enhance data integration, lakehouse capabilities, data freshness tracking, and dataset trustworthiness. Key improvements include PostgreSQL failover certification, MySQL performance boosts, expanded DDL history support, and updated data type mappings. Snowflake projects gain lake-landing ingestion for low-latency replication and Iceberg table support for flexible storage.

A new Freshness Indicator provides real-time dataset updates, while Qlik Trust Score™ (0-5) measures data validity, completeness, discoverability, and usage, ensuring greater transparency and trust in your data.

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WANT TO KNOW MORE? CONTACT US!

Roger Gray

BI Manager
roger.gray@climberbi.co.uk
+44 203 858 0668

Tom Cotterill

Senior BI Consultant
tom.cotterill@climberbi.co.uk
+44 203 858 0668

Published 2025-03-17

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