I am working in data analytics. They are the best solutions in the industry. With Qlik Sense, there is a way to integrate it within the company for sharing. It is good for certain use cases, though there are positives and cons for it as well.

I am working with QlikView mainly, and with Qlik Sense, the whole Qlik environment. It is licensed by the company I work for.

QlikView is highly manipulable, so you can build on top of the environment they already have to create your own solution for the problems you have. That is the positive for it compared to something Power BI.

Everything depends on the use case, but I would prefer Power BI because of how mainstream it is.

There is not much information available. It is not a mainstream tool that many companies use, so if you are doing something that has not been done before, you can find it challenging to get an answer. Unlike Power BI, where there are many examples of what you want to do elsewhere, with QlikView this is not the case.

The support for it could be improved. Growing the support online would be beneficial for Qlik. Having more guides on complex tasks you want to do with Qlik would help. There is support online and a Qlik community that shares solutions for common problems, but for quite niche requirements, it does not have that sort of support.

It has been almost a year now.

When the company I work for was installing the environment, it took them a long time to do it. The company did not have the scale to get it up and running efficiently. It took them a year or two to get everything working properly because the way we use it in the company is very specific to our professional services. It took them a while to get it working the way they wanted it.

Power BI has the edge on scalability. The Microsoft environment has the advantage because of its size. It is easily scalable with Microsoft, with other services Azure and other tools they provide.

I have never contacted Qlik myself.

Positive

It is based on SQL and T-SQL mainly, so if you are experienced with those languages, you would find your way easily.

It is not about performance. It is just about how expensive it is to implement.

For the company I work for, I have heard that Power BI would be a cheaper environment. That is why they are moving forward by integrating Power BI.

I think something Power BI has the edge over Qlik Sense. I am not working directly with certain aspects, so I cannot comment further on those. On a scale of 1-10, I rate this solution a 7.

I remember that a pharma company wanted a BI solution to represent or to create their own reports based on the data from Qlik Sense and the customer data.

Qlik Sense is not meant for writing something from the user interface, which is a major challenge because our company wants users to interact with the reports and to input some comments or data that should get stored into some database. The aforementioned area can be considered for improvement in the product.

With Qlik Sense, there is a need for it to provide good performance because if there is a large volume of data, then its performance becomes slow. User interaction or user experience is not that great in that case if the data size or reports are huge. The aforementioned area can be considered for improvement in the product. Right now, we are trying to follow up with some best practices recommended by Qlik Sense, but to be honest, it is not helping us much because we have very large data in a single application, and we are struggling with it.

The product should have an interactive and friendly user interface.

The use of APIs is not as friendly as it should be in the first place, especially when considering Python scripts and all other scripts, making it an area where improvements are required. There should be some easy way to integrate the product with the aforementioned areas.

I have been using Qlik Sense for four to five years. My company has a partnership with Qlik Sense.

There are no such issues with the stability or performance of the product.

Considering that I have worked with other products like Power BI, I don't see any scalability issues with Qlik Sense.

The user base is quite huge. For a single application, we have different dashboards or applications where the user base for applications or dashboards is different. In any case, the larger user base for a particular application consists of 200 or 300 users.

The solution's technical support is good. I rate the technical support an eight out of ten.

Positive

I have experience with Microsoft Power BI. Microsoft Power BI's self-service analytical capabilities are quite easy, which is a great addition to the product. For the data modeling part, I don't need a script, but with some drag and drop options, one can do it, but that is not the case with Qlik Sense since a user needs to have knowledge related to scripts.

It is not very easy to implement the product since you require some technical skills.

The solution is deployed on an on-premises model.

The time taken to deploy the solution depends on how complex the requirements are. For some use cases, considering the requirements, it may take six months to implement. If the requirements are easy, the tool can be implemented in a few weeks.

My company plans to switch from Qlik Sense to another solution.

Mainly, my company wants a product with writeback capabilities.

In terms of the areas that have proven to be the most useful in data analysis needs, I would say that I am currently looking for the writeback extensions now because something our company wants to input a few things from the reports and that should get stored either into the QVD files or either into the database directly.

The product is easy to use in our company, and it is used widely in our customer base. In my company, we don't see any issues with the product.

Trying to integrate Qlik Sense with other third-party solutions has been an issue for my company because the APIs that we use to integrate the tool with other solutions are not easy to use. In terms of APIs, the tool has become complex, and now our company is finding it difficult to integrate Qlik Sense with third-party tools, that has become quite complex for us because it requires the use of APIs, and it is not easy, especially when considering that we have limited knowledge of APIs.

I am not aware of the administrative side of the product since I mostly work on the technical part associated with it.

Whether I would recommend Qlik Sense to others or not depends on their use cases. If the data size and all those things are not the concern, I think Qlik Sense is a good solution. In some other cases, other solutions apart from Qlik Sense may be a good fit. I am not aware of the product from a functional point of view, but technically, if the user base and data size are huge, Qlik Sense can become problematic.

Speaking about how Qlik Sense supports our company's AI-driven decision-making processes, I can say that the tool currently serves our company's purpose, and we are currently looking deeper into the product since we want it to be easy to use and we also want the data size issues associated with the tool to the resolved so that it is able to fit into our needs.

My company did not exactly want the product to be integrated with other tools, but we did want to create and go for a mash-up, which can be accessed by other users, and I felt it was something that was difficult.

I rate the tool a seven out of ten.

My clients use Qlik for in-depth analytic analysis, creating touchboards for a variety of purposes. In our case, we prefer an on-premise solution over the cloud, especially for a banking client, to ensure data security and compliance with industry regulations.

One major benefit of having Qlik Sense in our organization is the ability to establish a strong KPI base. While various solutions offer similar capabilities, Qlik stands out for its remarkable speed, especially when compared to alternatives like Tableau. This speed advantage enhances overall efficiency in data analysis and decision-making processes.

The most valuable features of Qlik Sense are its speed and seamless development of web technologies. It is pure HDMI, eliminating the need for cache servers or translation engines, making it one of the fastest solutions compared to others. The direct connection between ML and data adds to its efficiency. Additionally, one standout feature of Qlik is its QVD data model, allowing the creation of data maps that are directly stored in memory, offering fast and efficient data service to consumers. Qlik's ability to handle large datasets with millions of rows is a significant advantage, although there are some limitations.

I would like to see improvements in the Qlik Sense SaaS version, particularly in the front-end capabilities. Currently, the visualization options are limited, allowing only basic actions like adding dimensions and measures with restrictions on the number. Compared to older products like QlikView, there is room for development in enhancing the features available on the front end for widgets and visualizations.

Enhancing the formatting options in the SaaS component and making it more visually appealing would be a nice enhancement. Additionally, expanding the library with more versatile widgets would be beneficial. While you can add components from a marketplace or develop your own, there is a need for Java front-end developers to handle this aspect of Qlik Sense.

I have been using Qlik Sense for four years.

Overall, Qlik Sense is stable, but there can be challenges related to managing the QVD data models, especially when dealing with numerous versions for different periods. While it requires effort to maintain, the system itself is generally stable.

Scaling Qlik Sense is possible by adding more servers, and it is generally smooth for load balancing and disaster recovery. However, making changes to the model can be time-consuming. Overall, it is scalable with effective load management and recovery mechanisms.

Setting up Qlik Sense is easy, especially for default visuals, though coding may be required for more specialized charts. Converting from QlikView to Qlik Sense is seamless for data models. The deployment process involves using Qlik Desktop for model development and two subscription options: on-cloud, which is ready to use, and on-premise, requiring Qlik Sense servers. Maintenance is simplified with admin tools, making it accessible for a developer. 

On average, for a consultant company creating reports and delivering a sales model with about five reports, the deployment of Qlik Sense can typically be handled within three months.

We have seen ROI with Qlik Sense.

Qlik Sense is pricier than other BI tools, with various licensing models, including potentially expensive token-based licenses. Organizations should carefully assess their budget and licensing requirements before choosing Qlik Sense.

Comparing it with other BI tools, Qlik Sense stands out by requiring a front-end developer for optimal project development. Unlike Power BI, which needs BI developers, or Tableau and SAP BusinessObjects that don't require Java developers, having a front-end developer enhances the project quality in Qlik Sense.

Before implementing Qlik Sense, my advice is to carefully assess its development needs, as custom components may require coding. While the deployment phase is generally straightforward, take advantage of Qlik Sense's flexibility in data modeling, allowing developers to write scripts for more tailored solutions. It is crucial to document projects for better collaboration among developers. Overall, I would rate Qlik Sense as a seven out of ten.

I use the product to teach data visualization at a university.

The product responds fast for data analysis.

The product could be less expensive.

It is a stable product. I rate its stability an eight out of ten.

I rate the product's scalability a five out of ten. It depends on the number of servers.

The technical support services are good.

Positive

I have worked with Palo Alto and Power BI.

The tool is very easy to set up. It took me nearly two hours to complete the proof of concept. It requires a couple of days to deploy it in a productive environment.

The product is expensive compared to Power BI. I rate its pricing a nine out of ten.

It is a very good tool for on-premise data analysis. I rate it a six out of ten.