Chapter 13. Demographic Data Discovery

In this final chapter, we shall finish our exploration of real data with Qlik Sense by moving beyond the standard structures of the office and showing the full possibilities of the software for analysis of almost any kind of imaginable data. We'll therefore be looking at applying Qlik Sense to demographic data. As before, this example and many others are available for you to explore at http://sense-demo.qlik.com.

This chapter will cover the aspects necessary for demographic data discovery, including:

• General information about common KPIs

• Examples showing how to use the lasso selection in maps and scatter charts

• Examples of dimensions and measures

Problem analysis

With Qlik Sense, it is possible to analyze not only business data, but rather any data. One great example is demographic data—statistics of countries and regions on anything from age and gender to income and life expectancy.

Such data can be found on a number of Internet sites and downloaded for your convenience, for example, from the following websites:

• United Nations (data.un.org)

• Federal government of the United States (www.data.gov)

• European Union (ec.europa.eu/eurostat)

• Qlik DataMarket (www.qlik.com/us/explore/products/qlik-datamarket)

Demographic data is used and analyzed as-is by a number of nongovernmental organizations that need it for their activities. The common measures required are GDP per capita, population, unemployment rate, inflation, life expectancy, happiness, trade balance, labor cost, national debt, election results, and so on.

Often, interesting questions about correlations are asked; for example, how does happiness correlate with material standards and health...

Application features

On our demo site, we have an app with a number of demographic measures per country. You can find it at http://sense-demo.qlik.com under the name Happiness. It analyzes, among other demographic indexes, the Happy Planet Index (HPI) in a number of countries. You can learn more about this index at www.happyplanetindex.org.

This index measures the sustainable well-being of 151 countries across the globe, focusing not on their abilities to produce material goods and services, but rather on their abilities to produce long, happy, and sustainable lives for the people who live in them. A happy life doesn't have to come at the expense of our environment, and the HPI is used to promote a policy that puts the well-being of people and the planet first.

The app overview of the Happiness application

Below this overview, you will see a number of sheets. The leftmost sheet is an introduction, whereas the other sheets are prepared for analysis and detailed information.

If you click on the...

How the application was developed

The data model of the Happiness application is not very complicated:

This is an extremely simple data model that only contains one table of real data, Happy Planet Index, and an additional table listing all countries, World.shp/Features. The second table has one record per country and holds the map information—the shapes of the country—used in the map object in the user interface.

In this app, the data table has exactly one record per country—a record that contains the relevant information for a given country at a given moment. However, this is not always the situation. More often, the data table contains data for countries over many points in time, for example, one record per combination of a country and a year. This will result in several lines per country.

Dimensions

There are not many fields that can be used as dimensions. The three available fields are region, subregion, and country. The world is split into 7 regions and 19 subregions. A country can only...

Summary

The analysis of demographic data is easy when you use Qlik Sense. Obviously, this analysis can also be made with a number of other tools, since the data model is very simple. However, with Qlik Sense, it is easy to build further. Qlik's associative indexing engine powers the analysis and ensures that you can develop or change your apps quickly and easily. With Qlik Sense, data discovery and analysis is made easy.

With the end of this chapter, we have also reached the end of the book. We took you from the history of Qlik to how to develop applications, and finally gave you some examples of how applications might look.

We hope that after reading this book, you have acquired some skills that will be useful when you develop your own Qlik Sense applications. We also think you now have a better understanding of the thoughts behind Qlik Sense, and wish you good luck in your endeavors.

Welcome to the community of Qlik users!