The most valuable feature of Qlik Analytics Platform is its Change Data Capture capability. This CDC function excels at reading logs from the original data sources and capturing transactions, almost in real-time. It essentially replicates this data into a secondary database, which is incredibly powerful for ensuring data consistency and availability. Besides that, the platform offers a user-friendly interface and a variety of data visualization tools that make data exploration and analysis a breeze. However, it is the CDC feature that truly stands out as a game-changer in terms of data replication and reliability.
One area where Qlik Analytics Platform could be improved is in providing better support for batch processing and traditional ETL workflows. While it excels in real-time replication, it lacks robust tools for handling batch data processing. This limitation can be challenging when there is a need to create non-real-time, batch pipelines for data integration and transformation.
I have been using Qlik Analytics Platform for three years.
The stability of the platform is generally reliable once it is deployed, regardless of the deployment timeline.
The initial setup is fairly easy. The deployment time for the platform can vary significantly depending on the nature and scale of the project. For larger enterprises like big banks requiring extensive data replication, it might take years to fully deploy. Smaller companies with simpler data needs could potentially deploy the platform in a matter of days. The timeline largely depends on the project's complexity and the amount of data involved.
Qlik Analytics Platform faces tough competition from major cloud providers. These cloud companies are moving customer data to the cloud and providing all-in-one solutions that include data integration, much like what Qlik offers. This puts cloud providers at the forefront of data projects. The challenge for Qlik is that organizations usually prioritize choosing their preferred cloud data storage solution, leaving Qlik as a secondary consideration for integration tools.
My advice to new users considering Qlik Analytics Platform is to carefully assess their data project needs. While Qlik is a solid on-premises platform, the trend in the industry is moving toward cloud-based data solutions, including data warehousing and integration. Cloud data warehouses are often more modern, feature-rich, and scalable. If you are planning to create a new data warehouse in the cloud, it might make sense to also opt for cloud-native integration tools.
The tech world is shifting towards cloud-native solutions, which better match the direction most global data projects are heading. Overall, I would rate Qlik Analytics Platform as a seven out of ten.
