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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.
The use cases depend on the industry. Finance, Telco, Manufacturing & Consumer Goods (CPG). Most of our customers are from these industries. We have regular projects in Mexico. Some use cases are around government requests to all banking and financing institutions, as well as public companies, to present specific reports every month. We use the solution to generate the reports for our customers. The sales and finance areas have a lot of requirements for such reports to get insights and predictive analysis.
We use Qlik Sense to manage all our sales KPIs as well as renewal plans. It's the tool where all the Go to Market plan is designed and modeled.
Reporting and Alerting are valuable features of the solution. Many companies are requesting to implement them and now want to explore and use AutoML. It is a machine learning module easy to use with enough capacity to run sales/churn models.
Adoption experience is required. There is some technical background required to do some of the reporting. Customers often request easy interaction with other tools like Excel and PowerPoint.
My organization has been partners with the product for more than ten years.
Two of Qlik's main differentiators are scalability and analytics capabilities. It could solve extensive data size dB.
I rate the support an eight or nine out of ten from the customers' perspective. The platform and the solution itself are quite stable, most of the support requirements are around getting the best usage of the solution.
Positive
The initial setup is quite simple. The setup and integration with the customers can be done fast. The deployment method depends on the industry. It can be deployed on-premises and on the cloud. Banking customers request to have the product deployed on-premise. We have around 50% of the product on-premise and 50% on the cloud.
The deployment takes less than a month. Most of the time, it takes one to two weeks to do the connections and create at least one dashboard in place. Then, depending on how deep the customer would need the reporting to be, it will take longer. It takes mostly two weeks for the setup, dashboards, and getting connectivity ready. We probably need one or two system engineers or IT engineers to deploy the product, no more than that. We have a lot of guys who have good experience with Qlik.
Upfront seems to be the most expensive tool. But when we talk about TCO, then the pricing rate change as this is one "all-inclusive tool" and does not need to add other services/elements to complete the setup.
We see more requirements around machine learning and predictive analytics. The customers could optimize the value for their money and increase ROI by using and getting most of the functionality in place. Most companies initially use the product as a dashboard tool, but if you do that, you are not getting the real value of it. Overall, I rate the tool a nine out of ten.
