QlikView extensions and the cycle plot
by Karl Pover, Stephen Redmond, Barry Harmsen, Miguel Angel Garcia
QlikView: Advanced Data Visualization
- QlikView: Advanced Data Visualization
- Table of Contents
- QlikView: Advanced Data Visualization
- Contributors
- Preface
- 1. Performance Tuning and Scalability
- Reviewing basic performance tuning techniques
- Generating test data
- Understanding how QlikView stores its data
- Strategies to reduce the data size and improve performance
- Testing chart performance for different load options
- Optimizing chart calculation times
- The QlikView calculation engine
- Using Direct Discovery
- Testing scalability with JMeter
- Running an example execution
- Summary
- 2. QlikView Data Modeling
- Reviewing basic data modeling
- Dimensional data modeling
- Differentiating between facts and dimensions
- Understanding the grain
- Understanding star schemas
- Summing with facts
- Discovering more about facts
- Dealing with nulls in fact tables in QlikView
- Designing dimension tables
- Defining Kimball's four-step dimensional design process
- Learning some useful reusable dimension methods
- Creating dimensional facts
- Handling slowly changing dimensions
- Dealing with multiple fact tables in one model
- Drilling across with document chaining
- Summary
- 3. Best Practices for Loading Data
- Reviewing data loading concepts
- Understanding why you should use an ETL approach
- Using an ETL approach to create QVD data layers
- Mastering loading techniques
- Using QlikView Expressor for ETL
- Summary
- 4. Advanced Expressions
- Reviewing basic concepts
- Understanding Dollar-sign Expansion
- Using advanced Set Analysis
- Calculating vertically
- Summary
- 5. Advanced Scripting
- Reviewing the basic concepts
- Counting records
- Loading data quickly
- Applying variables and the Dollar-sign Expansion in the script
- Using control structures
- Examining advanced Table File Wizard options
- Looking at data from different directions
- Reusing code
- Summary
- 6. What's New in QlikView 12?
- 7. Styling Up
- 8. Building Dashboards
- User types
- Applying the DAR principle to Airline Operations
- Creating the Analysis sheet
- Creating the new Dashboard sheet
- Creating the Reports sheet
- Other charts
- Summary
- 9. Advanced Data Transformation
- 10. Security
- 11. Data Visualization Strategy
- 12. Sales Perspective
- 13. Financial Perspective
- 14. Marketing Perspective
- 15. Working Capital Perspective
- 16. Operations Perspective
- 17. Human Resources
- 18. Fact Sheets
- 19. Balanced Scorecard
- 20. Troubleshooting Analysis
- 21. Mastering Qlik Sense Data Visualization
- Index
If we are going to work with advanced data visualization in QlikView, we have to get used to working with extensions. We can either develop the QlikView extension ourselves or use open source extensions that are available in Qlik Branch (http://branch.qlik.com).
For example, we are presented with the challenge to find a better way to visualize year-over-year (YoY), week-over-week (WoW), or any other period-over-period analysis. The following line chart demonstrates how difficult it can be to compare a large number of periods:
A cycle plot (Cleveland, Dunn, and Terpenning, 1978) offers a alternate way to compare a large number of periods. The following cycle plot is a QlikView extension that displays the average sales by weekday in each month and compares it to the total average sales represented by a flat horizontal line:
Let's create this cycle plot in Sales_Perspective_Sandbox.qvw using the following steps:
- In the
Ch. 2folder of the book's exercise files, double-click theCyclePlot.qarfile. QlikView will automatically open and notify you that the extension has been installed successfully. - In
Sales_Perspective_Sandbox.qvw, activate WebView. - Right-click over an empty space and select New Sheet Object.
- Click Extensions Objects and drag the extension called Cycle Plot to a empty place in the sheet.
- Define the following properties to the cycle plot. The expression is
sum({$<_ActualFlag={1}>} [Net Sales])/count(distinct _KEY_Date)
We should now see the cycle plot similar to the one previously shown. We will continue to explore more QlikView extensions in later chapters.
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