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
Contributors
Preface
Index

Reviewing basic data modeling


If you have attended QlikView training courses and done some work with QlikView modeling, there are a few things that you will know about, but I will review them just to be sure that we are all on the same page.

Associating data

QlikView uses an associative model to connect data rather than a join model. A join model is the traditional approach to data queries. In the join model, you craft a SQL query across multiple tables in the database, telling the database management system (DBMS) how those tables should be joined—whether left, inner, outer, and so on. The DBMS might have a system in place to optimize the performance of those queries. Each query tends to be run in isolation, returning a result set that can be either further explored—Excel pivot tables are a common use case here—or used to build a final report. Queries might have parameters to enable different reports to be executed, but each execution is still in isolation. In fact, it is the approach that...