In short, Qlik Sense is an application to help nontechnical users perform data visualization, analysis, and storytelling, within a governed environment. In this self-service BI tool, users can create simple data models and metric calculations without writing, or even seeing, one line of code. Also, Qlik Sense automatically generates cleaner, more intuitive visualizations without the need to memorize a myriad of property options.

As each new version is released, more and more features will be added to simplify tasks that were once only possible through coding. However, there will still be the need to code the more advanced data models and metric calculations. For example, users with technical aptitude will still be needed to facilitate the advanced analysis that we've seen in this book.

How we develop the load script and chart expressions remains largely unchanged between Qlik Sense and QlikView. Therefore, many data visualization tips and tricks that depend on manipulating the script, a calculated dimension, or a measure expression will work in both tools. On the other hand, Qlik Sense's chart objects have been built anew from the ground up, and they have no direct relationship to the ones in QlikView. Therefore, any tips or tricks that involve a particular chart property option in QlikView will most likely not work in Qlik Sense.

Even though Qlik Sense's chart objects currently offer fewer customizable properties than QlikView's, we can expect more property options to be added with each new version. However, as Qlik Sense's design intent is to be one that nontechnical users can easily manipulate, it would be unlikely that its property dialogs will reach QlikView's complexity or flexibility. Therefore, if we limit ourselves to employ only what is natively available in Qlik Sense, we will fail take full advantage of the opportunities that it offers.

For this reason, it is important that we change how we approach Qlik Sense. There won't be many opportunities to resolve our challenges by playing with an object's property options. So, the primary solution to most of our problems will be to develop a new, or edit an existing visualization extension. If we are not familiar with JavaScript, HTML5, and CSS, then we will need to invest time to learn these web programming skills. Such investment is more worthwhile when we see how it can also create opportunities to use Qlik-supported data analytics outside of Qlik Sense.

Qlik Sense is, in fact, only an example of what one could build on top of the Qlik Analytics Platform (QAP), a developer platform that gives us the opportunity to use Qlik's associative data model to address any data analytics need. We can use QAP to embed custom data analytics into existing applications or create our own personalized analytical tools. For example, we can embed data analytics in our customer or supplier portals, our ERP, or our CRM.

Although we can also create extensions in QlikView, we can never make them as powerful as native chart objects. However, QAP gives us access to the same APIs that Qlik uses to develop Qlik Sense, so visualization extensions can be just as robust. In the following section, let's take a look at an example of how we can use a visual extension to help sales representatives discover cross-selling opportunities.