Qlik Data Integration enable you to automatically produce real-time transaction streams into Kafka. Take advantage of modern analytics and microservices, enabling streaming analytics as well as streaming ingestion into data lakes and data warehouse platforms. And unlock the potential of data from legacy systems with microservices environment integrations.
To build a high-performing data lake, you need a solution for handling the labor-intensive manual engineering tasks that have traditionally slowed data delivery to a crawl. In other words, you need automated data integration, transformation, and cataloging. And that’s exactly what Qlik provides, when you use Qlik Data Integration with Databricks.
Qlik is now equipped to help customers meet their HIPAA regulatory requirements. US Healthcare organizations can now take full advantage of Qlik Cloud to enhance patient outcomes, improve service delivery, and close the gaps between data insights and actions. Qlik has completed the SOC2 Type 2 + HITRUST Attestation and have recently launched Customer Managed Keys, an additional security offering that allows customers to retain control of their data’s encryption when stored at rest in Qlik Cloud.
Did you know that Qlik offers a variety of monitoring applications that can provide various insights on your Qlik Cloud environment? If you want to track usage capacity of users on your tenant, check out the Entitlement Analyzer. Need to optimize your Qlik Sense applications? Then perhaps the App Analyzer will help. Want more insight into your app reloads – download the Reload Analyzer.
Customer Managed Keys allows customers to protect their sensitive data in Qlik Cloud, by using their own encryption keys provided by AWS Key Management Services - in the first phase of this release - giving them complete control over data encryption in their Qlik Cloud tenant.
Qlik Cloud Data Integration is a flexible fabric designed for data engineers to deliver, transform, and unify enterprise data in real time via automated, governed, and reusable data pipelines. These pipelines improve data timeliness, reliability, and scale, which are essential for every analytics, ML, or digital transformation initiative.