Book Image

Qlik Sense Cookbook - Second Edition

By : Pablo Labbe, Philip Hand, Neeraj Kharpate
Book Image

Qlik Sense Cookbook - Second Edition

By: Pablo Labbe, Philip Hand, Neeraj Kharpate

Overview of this book

Qlik Sense allows you to explore simple and complex data to reveal hidden insight and data relationships that help you make quality decisions for overall productivity. An expert Qlik Sense user can use its features for business intelligence in an enterprise environment effectively. Qlik Sense Cookbook is an excellent guide for all aspiring Qlik Sense developers and will empower you to create featured desktop applications to obtain daily insights at work. This book takes you through the basics and advanced functions of Qlik Sense February 2018 release. You’ll start with a quick refresher on obtaining data from data files and databases, and move on to some more refined features including visualization, and scripting, as well as managing apps and user interfaces. You will then understand how to work with advanced functions like set analysis and set expressions. As you make your way through this book, you will uncover newly added features in Qlik Sense such as new visualizations, label expressions and colors for dimension and measures. By the end of this book, you will have explored various visualization extensions to create your own interactive dashboard with the required tips and tricks. This will help you overcome challenging situations while developing your applications in Qlik Sense.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
Packt Upsell

Combining set analysis with Aggr

This recipe will show you how to use set analysis with aggregation functions combined with Aggr().

Set analysis modifies the behavior of the filters in an aggregation expression. When using Aggr(), you have two aggregations, one inside Aggr() and the other outside Aggr(), as in the following example:

= Max( Aggr(rank(Sum(Sales)), Country)) 

Where to insert the set analysis expression? Will the result be the same?

This recipe will show how the set analysis in the inner or the outer aggregation affects the result.

Getting ready

For this recipe, we will reuse the data load for the Using nested aggregation recipe from ealier in this chapter.

How to do it…

  1. Drag a Table object.
  2. Add the text, Europe Rank, as the object title.
  3. Add a dimension: Country.
  4. Uncheck the Include null values property.
  5. Add a new measure with the following expression, with the Regional Rank label:
= Max( Aggr(rank(Sum( {<Region={'Europe'}>} Sales)), Country))
  1. Add the second measure with the following...