Book Image

QlikView: Advanced Data Visualization

By : Miguel Angel Garcia, Barry Harmsen, Stephen Redmond, Karl Pover
Book Image

QlikView: Advanced Data Visualization

By: Miguel Angel Garcia, Barry Harmsen, Stephen Redmond, Karl Pover

Overview of this book

QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. Each chapter in this Learning Path starts with an understanding of a business requirement and its associated data model and then helps you create insightful analysis and data visualizations around it. You will look at problems that you might encounter while visualizing complex data insights using QlikView, and learn how to troubleshoot these and other not-so-common errors. This Learning Path contains real-world examples from a variety of business domains, such as sales, finance, marketing, and human resources. With all the knowledge that you gain from this Learning Path, you will have all the experience you need to implement your next QlikView project like a pro. This Learning Path includes content from the following Packt products: • QlikView for Developers by Miguel Ángel García, Barry Harmsen • Mastering QlikView by Stephen Redmond • Mastering QlikView Data Visualization by Karl Pover
Table of Contents (25 chapters)
QlikView: Advanced Data Visualization

Customer stratification.

Many of the user stories that we take into account when we start to use more advanced data analysis and visualization techniques are not new. For example, we have probably already used basic QlikView methods to resolve the following user story.

The simplest way to define customer importance is to base it on how much they've purchased or how much profit they've generated. In its simplest form, we can resolve this user story with a bar chart that ranks customers by sales or gross profit.

However, given our increasing experience with QlikView, we'll take another look at this user story and use a more advanced analysis technique called customer stratification. This method groups customers according to their importance into bins. The number of bins can vary, but for this exercise we will use four bins: A, B, C, and D. We use two techniques to stratify customers. The first technique involves using the Pareto principal, and the second involves using fractiles.

Pareto analysis...