By now we have a data model, a styled frontend, and a layout design. It's now time to populate our document with charts, tables, and other data visualization objects.
We will first look at the various types of QlikView users, and what they typically look for in a QlikView document. After that we will look at the different chart options available, along with a few other sheet objects, and use them to extend our dashboard. We will also take a more in-depth look at the ways in which we can create basic calculations in the various objects.
Specifically, in this chapter you will learn:
- The three basic types of QlikView users, and how best to cater to their needs
- The various charting options available in QlikView
- Other sheet objects that can be used to add interactivity to our QlikView documents
- How to create basic calculations
Let's get started!
The data model within a single QlikView document can be used to serve the information needs of a wide range of users, from the executive to the operational level. As different user groups have different information needs, QlikView documents are often built using the Dashboards, Analysis, and Reports (DAR) approach. Of course, with a limited number of user types, it is inevitable that they are painted with a broad brush. Most QlikView users will fall into more than one user category. Let's take a look at each of them.
Dashboards offer a quick, bird's-eye view of information. They are often used by executives and middle-management to gauge performance of a limited number of Key Performance Indicators (KPIs) against predefined targets.
Data displayed in dashboards is usually aggregated at a high level. Drill-downs to more granular data, while technically not a problem in QlikView, are purposely limited. When dashboard users spot an anomaly in the data, they may simply ask an analyst to dig deeper.
Typical data visualization on a dashboard includes speedometers and traffic lights to provide, at a quick glance, the current status of the defined KPIs. The following screenshot depicts a typical, albeit cleanly formatted, dashboard:
While dashboard users commonly want to have a general view on their performance at a glance, analysts are the ones who really dig into the data. They will try to uncover not only what happened, but also why it happened. To do this, they require access to the complete dataset with no detail left out; they also need to be able to query it in many different ways.
In QlikView, this translates to having several listboxes for easy data filtering, along with many different charts offering comprehensive and insightful views of the data. Many analysts will also create their own visualizations whenever they need to answer a specific question, or will make extensive use of What-If scenarios to test and predict an outcome based on changes in certain variables.
Typical data visualizations used in analysis include scatter, bar and line charts, and pivot tables. The following screenshot shows an example of a typical analysis sheet:
In QlikView, reports are considered to be more or less static displays of information in a tabular form. Reports can serve multiple purposes; for instance, they can be used to provide users at the operational level with the information they need in their daily activities. They can also be the end-point of an analytical exercise.
Typical data visualizations at the report level are straight tables and pivot tables. The following screenshot shows a typical report:
