Data visualization is a powerful analytical technique and an exciting form of communication. Only in the past few decades has the advent of the personal computer helped it become a more widely used method to explain events, investigate cause-effect relationships, and search for opportunities among growing amounts data.
Data visualization has come a long way since being used solely as eye-candy on top of tabular spreadsheets. Slowly, but surely, we are coming to realize that flashy 3-dimensional charts are neither evidence of a particular software's effectiveness nor of a well-executed analysis. Instead of glitzy graphs, we are now looking for ways to quickly and easily create insightful data visualizations in software that complements our thought processes.
QlikView has been that software for thousands of empowered business users. The ability to rapidly produce powerful analysis and data visualization on top of a data model developed to imitate human thought has placed QlikView at the vanguard of data discovery tools.
QlikView lends the responsibility of choosing the most suitable data visualizations to us. In real world implementations, the freedom to choose how data is visualized has minimized the resistance to the change brought on by migrating old, static corporate reports, and spreadsheets to a new platform. However, we need to grow and learn how to create the best data visualization that allows us to fully benefit from QlikView's dynamism.
In the following chapters, we propose a data visualization style guide and apply it to various forms of analysis in QlikView. We will not cover all of the software's available visualization options, but rather we review a selected mix of both basic and advanced functions that covers the most valuable analytical techniques.
We pack as much content as possible into as few pages as possible to give you a quick return on your investment of time and money. The book is written to be read from start to finish, and then, used as a reference book for your own data discovery experience. We hope this book is part of a continual learning process to create great data visualization with QlikView.
Chapter1, First Things First, explains how finding the right people, data, and tools is key to creating great data visualizations. Finally, we start our first exercise in data discovery.
Chapter 2, Rank Analysis, explains how to use bar charts to create analysis that ranks values. We introduce the data visualization style guide.
Chapter3, Trend Analysis, helps us discover how line charts show us how our company has changed over time.
Chapter4, Multivariate Analysis, explains ways to analyze a large amount of variables using straight and pivot tables along with heat maps.
Chapter5, Distribution Analysis and Statistics, takes our analysis further by adding more sophisticated statistical analysis. We review the histogram, frequency polygon, and box plot chart.
Chapter6, Correlation Analysis, looks for relationships between variables using scatterplot charts.
Chapter7, Geographical Analysis, brings to light how location adds insightful information with a geographical chart. We introduce the use of extensions.
Chapter8, What-if Analysis, explains how to include variables that we can change to create possible future scenarios.
Chapter9, Dashboard and Navigation, brings everything together to communicate the results of our analysis. In the process, we propose a solution and create a way to monitor its execution.
You will need a computer and internet access to download QlikView and additional files required to perform the exercises throughout the book. Download the additional files in the Support section of http://www.packtpub.com/learning-qlikview-data-visualization/book. If you are using the QlikView Personal Edition, follow the instructions included in downloaded files before starting the exercises.
This book is for anybody interested in performing powerful data analysis and crafting insightful data visualization independent of their previous knowledge of QlikView.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text are shown as follows: "The resulting expression is Sum ([Net Sales])."
A block of code is set as follows:
if(Division='Government',Blue(200),RGB(150,150,150))
New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "Right-click on the new chart and select Properties…"
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