QlikView Reviews

The ability to build models that allow business users to do their own what-if analysis on the correct data.

The business was previously using Crystal running on top of hardcoded SQL stored procedures and Qlikview. Qlikview improves development productivity and allows self-help BI.

I would like to see more ‘drag and drop’ functionality as, in my opinion, there is still too much coding required to join tables correctly.

I have been using this solution for 18 months.

As mentioned, we previously used Crystal as well as Oracle OBIEE and both are inflexible and time-consuming.

Initial setup was very straightforward, plus the team had set up Qlikview previously.

We used a vendor team for implementation and that’s probably the way to go first time around, but there must be a skills transfer.

Qlikview are always willing to negotiate pricing, especially if you mention that you are evaluating Tableau as well.

Don’t believe the sales talk that you don’t need a datamart or data warehouse to run Qlikview on top of. It can run against ERP data but then the queries get very complicated and cumbersome.

It allows you to establish business data models on an associative basis, and to do on-the-fly analysis on associated data for deep understanding / insight.

For complex analysis, its scripting capabilities enable one to do complex calculation to present required information much easier than traditional / other BI software.

I have implemented both QlikView and Qlik Sense solutions for our customers/organizations in multiple industries.

The immediate improvements allow organisations:

• To analyse data more comprehensively (e.g. in the areas of risk management and customer profiling/segmentation) to provide greater insight / understanding
• To make data available more quickly to facilitate decision making, especially for exceptional cases (e.g. when not meeting KPIs)

Other side benefits derived from implementing such projects are:

• Data gaps: It can identify insufficient or unavailable data for making better decisions.
• Process gaps: It can identify business processes that need to be improved, e.g. manual processes that need to be fine-tuned or automated.
• System gaps: It can identify areas where the system needs to be improved e.g. improvement to existing system functions, or a new system needs to be put in place.

With such gaps and their relationship to the values of decisions, an organisation is able to prioritized resources to address those gaps over time.

Improve its table/data editor to allow easier ways to pull multiple data from multiple sources and associate them to establish a complete business data model.

Consider providing more features that allow the decision-making process of analysing different data at different levels to be captured. Maybe a decision-making flow/process editor for Qlik sheets and objects at the presentation layer.

I have used QlikView for approximately five years.

You can encounter deployment issues if you do not follow good / recommended “best practices”. Such issues can always be resolved through better design of the implemented solution.

By adhering to good practices, deployment, stability and scalability should not be an issue.

Technical support is average.

Initial setup is straightforward and much easier than other traditional BI software.

We are a Qlik implementation partner. We implement Qlik solutions for customers.

Our customers’ ROI is typically within 1-3 years, depending on the size and complexity of implementations.

Initial pricing/licensing of QlikView and Qlik Sense are competitive to the market. However, as the number of users grows, it could be costly.

You need to understand well the users’ decision-making process, the data requirements and the actions users want to take. It is OK to start a Qlik project without complete data available.

The associative engine and feature-rich expression scripts are the most valuable features of this product.

Easy, low-TCO solution to consolidate and visualise data for analysis and reporting purposes.

It provides better visibility of the company's position and its operations.

I would like to see more visualisation objects features.

I have used QlikView for more than a year.

I encountered minimal deployment issues.

Technical support is excellent.

I have experience with other similar visualizers, but QV offers a better experience in terms of ETL development.

Initial setup was straightforward, with a simple, easy interface. We had a simple setup anyway, not much complexity. We were able to get QV up and running in a very short turnaround time.

It was implemented in-house assisted by a lean vendor advisory team.

Data mining and consolidation are the products most valuable features to me.

I was using this to track KPI’s on my outsourced end user support (ticketing, resolution & time it takes to resolve). This forced my contractor to deliver because QlikView provides an analysis of the issues as they appeared.

I would like to see improvements to scheduled reporting and the capability to email the user.

I have used this solution for over four years.

I was using the cloud-based solution, so I didn’t have any issues.

Technical support was super, can't complain.

I had used other solutions, but they didn’t give me the kind of reporting & analysis I got from QlikView.

Set up was easy. Being technical, I found it easy and straightforward.

For our installation, we used the vendor. However, for my peace of mind and understanding, I was involved throughout the process.

ROI was not a consideration for me, though I would would say it was a great tool I would have equally gone for, even if it involved doing the ROI.

My use was more about service measurement & improvement.

The dynamic interactive dashboard is the most valuable feature of the product to me.

Lots of scripting used to be required to build high quality dashboards.

This cannot be considered a self-service product. It requires IT support.

I have used QlikView for one year.

This is quite a stable product, but very huge data loads must be complemented by good hardware. Otherwise, there could be performance issues.

Technical support is OK.

The only reason we chose this product is its dynamic interactive dashboard. It works well on iPad. We liked the product, as compared to MS BI.

Initial setup is quite straightforward, but it requires good hardware for high data loads.

An in-house team and a vendor team collaborated on the implementation.

It is quite expensive. There are two types of licenses: Named User licenses and Doc CAL licenses.

You need to have good scripting skills.

• Load script engine (or "ETL" ability)
• Connectivity integration options
• Data visualizations / dashboarding

As a start-up, projects need to move fast and this product has enabled us to have data solutions ready when the business needs it.

• Better compatibility with Qlik Sense
• Better support for non-Microsoft platforms
• SFTP support in the load script
• More built-in connectors

I have used it for three years.

We wanted to upgrade to version 12 but had two models that were not reloading as expected and had to revert.

Technical support is good.

We chose this product because we needed to connect to the source system and report directly from it.

It was already established when I started.

Initial setup was straight forward. The only challenge is maintaining a custom user directory by hand, because of a lack of Active Directory in the organization.

Now we do everything in house. At the very beginning, before I started, we had vendor support.

ROI is tricky to measure but I'll give some examples:

• Finance can now do month-end statements in one day instead of seven.
• We can determine if a new product in a new market will be profitable within weeks of launching a pilot.
• Engineering is free from having to run database queries to answer business questions.

You need at least as much RAM on your server as the largest database table you will read, and it can't be a virtual installation.

• The in-memory engine is really powerful, making it possible to deal with huge data records on the fly (more than 400 million in a table). I have built data models with over 1 billion records and the performance is good.
• With in-memory calculations at the UI (on the fly), it is possible to build charts, tables, etc. directly on the user interface (UI).
• Cubes are built on the UI. No need to pre-aggregate data, but it is of course possible to do that in the script (which I would not recommend) or better deliver data as SQL-View.
• Scripting possibilities to build complex applications and functionality.
• Web integration capabilities, for ex. you can include JScript Objects or R for better visualization.

We are service providers and built applications for our customers, not for us. Our customers are able to evaluate their marketing campaigns at the aggregated and customer levels. They can use micro-segmentation to select the leads.

We actually use QlikView, which does not allow easy-to-use framework management. There is a deployment framework, which I do not find easy to use and somehow not stable. I hope QlikView can improve this.

I have been using this solution for 3.5 years now.

There is no general rule, but we use the deployment framework, which allows us to produce a QV application user with four different levels of deployment:

• One level for the extraction of the data (1 to 1)
• In the second level, we get the original tables and based on the user requirements, build the data model and make the necessary transformations.
• In the third level, we get an intermediary state of the data model to be loaded in the end-user application.
• The fourth level contains the end-user application. We do a “binary” load, which is a command line in the QlikView script that allows us to copy 1-1 to the application we are copying from, in this case, from the third level. We have separate development from production and testing in a highly reachable environment (cluster environment).

It is stable, but of course stability depends on your IT infrastructure and deployment chosen.

Data model, data size, RAM size, hardware CPUs and UI expressions / charts, are strongly related. It is possible to scale QV without problems, but the issue is more complex than not having enough RAM. Complex expressions at the UI level, single threaded object calculations, complex data models, huge data size, etc., can alter the performance of the QV application and thus we might think we need to scale. There are many tools to measure QV performance and to try keep them at an optimal level. Otherwise, if everything else is fine, we need to increase RAM. Actually, we have 1 TB RAM on our production server.

Technical support is good, but could be improved.

Initial setup was straightforward. You need a server, install QlikView with its web server option and then you can start doing applications.

For more complex architectures (clustered, with two or more servers), you will probably need Qlik Tech support.

We contacted Qlik Tech directly for a cluster implementation (at my current company).

Pricing/licensing depends on your company size, the uses of QV, # of users, among others. Named CALs, at approx. 1.200 EUR (see the Qlik website), would be required if you have permanent users with write access to different applications, while Document CALs are good if you have users that will only see a document to perform their jobs. There is good and simple documentation explaining your best pricing / licensing model.

For my previous company I compared Tibco, QlikView, Tablaeu, and other tools, as indicated in the Gartner Quadrant. We did workshops with them, and were happy with QV because you can build something immediately. In the case of Tablaeu, you need a really well-established ETL and / or views. Otherwise, it is complicated for a normal user to build correct charts. Users have normally very little understanding of the data structure. Other tools need pre-aggregation and a long development process. With QV, it is possible to use views, pre-aggregated or raw data and you can still manipulate the data in the script, i.e. do ETL (see Deployment Framework).

1. Check your user and business requirements first and check if QV can help you solve your user / business needs.
2. If yes, check what are the potential uses of QV and describe the environment, company or unit size, # of users, # of applications, # of KPIs, and data volume. After this first check, you may be able to determine how big would your applications be, and thus estimate current and future RAM, necessary IT Infrastructure, # of servers, etc. I would talk to IT to see how to integrate QV into your IT environment. Many people start with an isolated QV implementation in their unit, which is fast, but then you have no single point of truth (this may discourage adoption because the user does not trust the data). But it depends on your goals.
3. Start working and promote user adoption, showing good functionality, fast implementation, and reliable data. QV can then become the main BI tool in the company.
4. Looking forward, QV can be extended in the use of mash-ups, Jscript extensions and analytics with R, so that you can build up in the future. Qlik Sense is a new Qlik Tech product, which offers many new possibilities.

QlikView's associative data model is the key feature of this application, which makes it superior amongst other competitors. It eliminates left, right, inner joins, and takes care of creating links between different tables.

Other valuable features are the Power of Gray, on-the-fly data cloud creation, and its ease of use and deployment.

With the Power of Gray, QlikView shows you what you are doing and what you are not doing.

New graph / chart objects need to be added.

I have used QlikView for the last four years.

Deployment with a big data cloud is a challenge so far.

Technical support is very good.

Initial setup was straightforward.

Before you start implementing it right on your computer, you have to design the data model on paper. Once you have an error-free data model on paper, you can finish the project earlier than planned.

Pricing and licensing depends upon the offer made by the vendor. However, QlikView ROI is extensively very high. We have seen it when we receive upsell requests from clients.

There are different tools in market, we have to differentiate between visualization and analytical tools , QlikView is analytical and descriptive tool.