The main use cases involve getting data in an analyzable format. Clients should be able to analyze it through a self-service tool, which is why Qlik Sense was the better choice. Self-service is the primary use case they had as clients wanted to perform self-service analysis.
Additionally, they wanted to automate workflows along with the analysis. They aimed to have action-driven analysis, focusing mainly on dashboard analysis and automated workflows depending on the analysis they perform.
The self-service capabilities that Qlik Sense offers are significant. They offer natural language processing, allowing users to ask questions in layman language, and Qlik Sense will create charts and narratives automatically. Users can access any dashboard developed in Qlik Sense from familiar portals such as Okta or other company portals through embedding features.
The integration with chatbots, particularly Microsoft Teams, allows users to access dashboards and ask questions directly within Teams. The collaboration feature enables users to share analysis by taking snapshots and tagging team members within the Qlik Sense interface, eliminating the need for lengthy emails or screenshots.
The storytelling feature allows users to create presentations directly in Qlik Sense using dashboard analysis, making it easier to answer questions during meetings. The subscription feature enables users to receive charts and sheets via email instead of navigating to the dashboard, facilitating monitoring purposes.
Qlik Sense offers alerting capabilities where users can set thresholds for KPIs and receive notifications when these thresholds are reached. The platform also includes AI/ML features for predictive modeling through a no-code component, allowing business users to create and deploy AutoML models without depending on data scientists.
The Qlik Answers component, featuring generative AI capability, enables users to get answers from unstructured data including Excel, HTML documents, or Microsoft Word documents by creating a knowledge base.
The user-friendly interface operates on a drag-and-drop approach, with Qlik Sense suggesting appropriate charts based on selected dimensions and measures. The associative engine capabilities allow data association between tables, implementing selections across related tables. The platform uses a color-coding system (white, gray, and dark gray) to show related, excluded, and unrelated data selections, providing insights beyond traditional BI tools.
The support aspect could be improved, particularly in terms of response time for high-priority issues, especially when dealing with production environment client issues that require immediate attention.
Qlik Sense Cloud pricing is relatively high. While on-premises versions work with user-based licensing effectively, the cloud version's capacity-based pricing needs more clarity. There should be more comprehensive documentation and explanatory videos available to help clients understand and calculate capacity-based pricing, making it easier to predict costs before implementing Qlik Sense Cloud.
I have been working with Qlik Sense for 10 years.
I have not encountered any deployment issues.
Qlik Sense helps analyze data and can handle larger amounts of data compared to other BI tools. Qlik Sense has never had issues related to large data sets. For deployment options, it works in two ways: on-premises and Qlik Sense Cloud. Qlik Sense offers a public cloud where dashboards can be hosted, which is becoming the more feasible option that most organizations are choosing.
Setup has always been straightforward. The Qlik Sense help site provides comprehensive information for setup support.
Most organizations had scattered data across many legacy systems. Qlik Sense has consolidated all the data in one place and provided answers to all their questions, helping to make better decisions and enabling faster collaborations.
If you have a scattered system and want to analyze your data, structured data, along with the unstructured ones, Qlik Sense is the best option where you can collaborate both data formats into one and perform analysis on top of it. This eliminates the need to rely on multiple systems to get answers.
On a scale of 1-10, this solution receives a rating of 9.