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

Working capital data model


The working capital data model can be constructed in a variety of ways. The most important feature of the data model is its ability to accumulate account balances over time. We accomplish this by adding an as-of calendar. However, we can also create a model that uses periodic snapshots and avoid accumulating individual transactions after every user selection. A periodic snapshot is a recurring event that saves a copy of the data at the end of every day, week, or month.

Note

Even though we may end up only using monthly snapshots in a QlikView application, it is wise to take a daily snapshot of the data and save it in QVD files in case business requirements change.

In this chapter, we will use a periodic snapshot to measure following events in the data model:

  • Month-end inventory balances by item and warehouse over three years

  • Day-end inventory balances by item and warehouse over the last the last three months

  • Month-end balances of A/R invoices over the last three years...