Qlik Cloud September 2024: what’s new

4. Expressions in field labels

You can now have expressions in field labels for drill-down and cyclic dimensions. This lets you for example enable translation of labels in multi-language apps.

Creating a drill-down dimension

Creating a cyclic dimension

5. Layout container improvements

Charts are now highlighted in the container when they are selected in the list in the property panel.

Layout container

6. Removal of Sheets button

Now when the transition to the new sheet navigation is complete, the Sheets button is going away. Use the Assets button on the left side instead.

7. Combo chart improvements

Based on feedback from our customers we’re improving the combo chart and adding labels to markers and a setting to toggle the grid.

Combo chart

8. Model Approval Workflow

Model Approval Workflow enables customers to “opt-in” for greater control over the activation of machine learning models when they are deployed on Qlik Cloud. This is enabled through the control of custom security roles.

Approving deployed models

9. Change to platform navigation

As announced on July 9th, the new platform navigation was released as an opt-in for a limited time. Today, it has become a default for all tenants without an opt-out.

This change brings significant user-experience improvements, such as more ease of navigation and finding your way around the platform, with a common anchor point in the waffle menu in the top-left corner throughout the whole platform.

This also includes the introduction of Activity Centers, with areas focused on consuming analytic insights and creating analytics with a new Insight Advisor Chat experience.

Qlik Cloud interface overview

Qlik Cloud Analytics activity centers

Qlik Talend Data Integration activity center

Innovation blog (Qlik Community)

Corporate blog

10. Print, subscribe, snapshot, and monitor with the new Pivot table

The new pivot table is now getting support for download as image and PDF, storytelling, subscriptions, and monitoring. We know many have been waiting for this and we’re glad to announce general availability. The new tables are rolled out with new features incrementally and will soon be moved from the visualization bundle to the native chart section

Visualization bundle

3. Target-based dataset model for transform and data mart tasks

To make pipeline design more flexible, we are introducing a new dataset model for transform and data mart tasks: the target-based model.

Data products are valuable because data product teams can quickly produce high-quality, curated, domain-centric data assets, that can be easily accessed by data consumers and leveraged in several business use cases across the organization. This closes the gap between what data producers are putting together and what data consumers need. Just like real products, data products are built iteratively and have a lifecycle – from creating a data product to managing the quality of the data product, activating it into the data marketplace, and deactivating it when they are no longer needed.

Key Features

Qlik Talend Cloud brings together an integrated data management experience – from data integration to transformation, data quality, and governance. The data product catalog in Qlik Talend Cloud offers several key capabilities to manage the data product lifecycle end-to-end.

• A data marketplace, where data products are readily available for data consumers to shop and leverage according to their use cases. Within the data marketplace, data consumers can get a sample preview of the data products, including quality information, descriptions, and relevant tags.
• Data product quality and profiling where data product teams can get a quick data sample, profile the data based on the different data types, and ensure the integrity of the data within the data product. In the case of Snowflake tables, data quality assessments are pushed down into Snowflake to optimize compute operations.
• Data product lineage and impact analysis allow users to trace the origins and transformations of data products. Understanding where the data came from and how it changed along the data pipeline enhances data trust and brings more transparency for data consumers.
• Integrated data catalog experience means that data products can be composed of datasets that are registered in the Qlik Talend Cloud catalog, streamlining the workflow for data product teams without requiring any additional tools.
• Data product access control through managed spaces simplifies access control for data products, emphasizing easy data sharing with data consumers within the Qlik Talend Cloud environment.
• Data product lifecycle management enables data product teams to treat data products just like real products, composing them from relevant datasets, evaluating data quality, assigning ownership, managing data product attributes (such as description, tags, and more), and launching them for consumption. If a data product no longer meets business needs, it can be deactivated.
• Data product consumption using Qlik Sense apps allows data consumers to easily load data products into Qlik Sense applications, enabling a seamless transition from data discovery to actionable insights with just a few clicks.

Working with data products

7. AI processor for transformation flows

A new processor has been introduced in transformation flows to make it easy to leverage your Databricks platform’s AI capabilities. The AI processor includes seven state-of-the-art generative AI functions:

• sentiment analysis
• grammar issues fix
• translation
• text summary
• string similarity
• data masking
• classification.

AI processor