Beyond visualizations, we have made usability enhancements to the Qlik Sense UI to provide a more fluid and natural user experience, using a tabbed metaphor across data, analytics and storytelling. We have added to our advanced authoring capabilities with a new addition to the Dashboard Bundle that allows sharing of insights via a direct link. Also, we have added new dollar sign expansion functionality to the expression editor allowing users to evaluate the results of calculations, which reduces the chances of a syntax error.
This release also includes several advancements in the mobile space, as we continue to empower the mobile workforce and drive our market leading mobile strategy. The February 2019 release includes a new Qlik Sense Mobile app for Android, and new support for mashups in Qlik Sense Mobile. We have also expanded EMM (Enterprise Mobile Management) capabilities with support for Microsoft InTune – one of the fastest growing EMM platforms in the market. Moreover, we are leading the pack in mobile threat detection security with new Zimperium integration. This release sets the foundation to drive our ongoing mobile strategy and future roadmap.
The February 2019 release also delivers highly requested features and quality improvements for several of our value-added products. Specifically, several highly sought-after features have been added to Qlik NPrinting, including image scaling for Qlik Sense analytics, and support for variables in emails – making it more capable of supporting a wide range of customer requirements and use cases.
Finally, we are thrilled to roll out the open GA of the Qlik Associative Big Data Index. This add-on product unlocks the value of large data sets by delivering the Qlik Associative Engine to the biggest data repositories; allowing our customers to freely explore and analyze without limits. The Qlik Associative Big Data Index provides a governed, scalable, high-performance associative experience that can be deployed within sources such as Hadoop-based data lakes, eliminating the need to transfer and prepare the data elsewhere before it can be analyzed. With this, we can confidently claim that big data is simply data to Qlik.
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