

QlikView and Google Data Studio compete in the data analytics and visualization category. QlikView seems to have the upper hand with its robust data management capabilities and in-depth analytical features, making it a preferred choice for handling complex business intelligence tasks, while Google Data Studio is noted for its user-friendly interface and seamless integration with Google services.
Features: QlikView provides robust data management, extensive scripting, and in-memory processing, making it ideal for handling large datasets. Its associative model allows for comprehensive data exploration and real-time analysis. Google Data Studio focuses on ease of use and accessibility, with seamless integration into Google's ecosystem for straightforward data visualization. It offers user-friendly, shareable dashboards and reports.
Room for Improvement: QlikView users face challenges with complex scripting, limited visualization capabilities, and high costs, needing enhanced AI features and better platform integration. Google Data Studio has limited data manipulation tools and basic visualization options, with dependency on Google services posing a barrier for non-Google data sources.
Ease of Deployment and Customer Service: QlikView requires complex on-premises deployment, though hybrid cloud setups are available, and customer support varies across its partner network. Google Data Studio uses the public cloud, allowing easy deployment with minimal setup, but support often depends on community resources, lacking enterprise-grade robustness.
Pricing and ROI: QlikView is more expensive, using licensing models that may restrict smaller businesses, but it's considered cost-effective when fully utilized for its features. Google Data Studio is free, appealing to budget-conscious organizations, although additional costs might arise from integrating other services.
The number of employees has reduced to half, and time is saved by nearly two to three hours a day because of automated reports.
The biggest return on investment is the time saving for the customer.
Anyone with minimal knowledge of Looker can easily go through the documentation and understand the steps and the UI.
I would rate the customer support a solid 10.
I am totally satisfied with technical support from Qlik.
I rate Looker's scalability a nine because of how easily we can scale by simply combining tables.
If you want better performance with a larger volume of data, you can simply add an additional server.
The performance is not optimal on large data sets.
AI features are already available in Qlik Sense, so you would need to migrate to that platform.
In QlikView, I believe the improvement that should be made is to bring the costs down, as you'll have to be competitive with Power BI, aiming for at least a 30% reduction to stop the hemorrhaging to Power BI.
The license cost per user or per year for QlikView is about 500 Euros annually.
I would rate the pricing for QlikView as not cheap, but it is reasonable.
For a business user to understand data from free form or Essbase, it usually takes thirty minutes to an hour to go through the previous day's trend. However, with the visualization tools in Looker, they can easily understand the data and compare it to the previous one or two years using a bar graph, pie chart, or other graphs.
Building metrics using simple language, similar to what you have in Excel, is what I have found most valuable in QlikView.
The best features in QlikView are rapid development, the fact that I can do what I want in QlikView, and full control along with ease of use.
| Product | Mindshare (%) |
|---|---|
| QlikView | 7.3% |
| Google Data Studio | 5.5% |
| Other | 87.2% |

| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 8 |
| Large Enterprise | 7 |
| Company Size | Count |
|---|---|
| Small Business | 73 |
| Midsize Enterprise | 36 |
| Large Enterprise | 76 |
Google Data Studio enables seamless integration with Google's ecosystem, enhancing data visualization with Looker's capabilities. Its semantic layer and real-time insights support efficient dashboard creation and sharing.
Google Data Studio offers comprehensive data management through LookML, allowing custom data modeling with minimal training. Its centralized data management facilitates dashboard creation for non-technical employees. Users benefit from real-time insights and advanced analytics, along with automated reporting that reduces workload. Although it offers customization and data-level security, areas like visualization flexibility and large dataset performance need improvement. Challenges include handling complex filters, limited chart types, and the absence of multi-sheet options.
What are the key features of Google Data Studio?Google Data Studio is implemented in industries like real estate, sales, and marketing for creating operational reports and understanding trends. It helps organizations visualize data for customer behavior analytics, supporting developers in managing integrations and data governance efficiently.
QlikView enhances data analysis with its associative data model and rapid in-memory processing, providing dynamic dashboards and robust visualization, while efficient data integration allows connections to multiple sources.
QlikView offers powerful analytics and insight generation capabilities through its integration with Salesforce, enabling real-time sales data access. Its customizable dashboards are complemented by scripting for complex calculations and QVDs for performance optimization. Designed to be user-friendly, it supports ETL processes and diverse data browsing, allowing users to interact with data intuitively. However, there is room for improving licensing complexities, scalability, and self-service functionality. Additional enhancements are desired in visualization, integration with Qlik Sense, and predictive analytics support.
What are QlikView's key features?QlikView finds use in building business intelligence dashboards across sectors, integrating with Salesforce for analytics, supporting financial planning, and tracking sales. Its intuitive interface aids manufacturing companies in KPI monitoring and informs commercial decisions. The tool enhances reporting, ETL processes, and diverse data source integration, facilitating offline data access.
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