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

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QlikView: Advanced Data Visualization
Miguel Angel Garcia | Barry Harmsen | Stephen Redmond | Karl Pover
Dec, 2018 | 13 hours 6 minutes
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Table of Contents (25 chapters)
QlikView: Advanced Data Visualization
QlikView: Advanced Data Visualization
Contributors
Contributors
Preface
Preface
Free Chapter
1
Performance Tuning and Scalability
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
QlikView Data Modeling
Reviewing basic data modeling
Dimensional data modeling
Handling slowly changing dimensions
Dealing with multiple fact tables in one model
Drilling across with document chaining
Summary
3
Best Practices for Loading Data
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
Advanced Expressions
Reviewing basic concepts
Understanding Dollar-sign Expansion
Using advanced Set Analysis
Calculating vertically
Summary
5
Advanced Scripting
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?
What's New in QlikView 12?
Common QIX Engine
What is new in the Qlik product portfolio?
How do the products in the Qlik product portfolio fit together?
Summary
7
Styling Up
Styling Up
Design requirements
The Document Properties window
The Sheet Properties dialog
Setting the object properties
Working with listboxes
The Multi Box
The Current Selections Box
Adding a Bookmark Object
Aligning and resizing sheet objects
Creating and applying a default color map
Summary
8
Building Dashboards
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
Advanced Data Transformation
Data architecture
Loading data already stored in QlikView
Aggregating data
Sorting tables
The Peek function
Merging forces
Dealing with slowly changing dimensions
Ordering, peeking, and matching all at once
Incremental loads
Summary
10
Security
Security
Hidden script
Section access
Document-level security
Sheet-level security
Summary
11
Data Visualization Strategy
Data Visualization Strategy
Data exploration, visualization, and discovery
Data teams and roles
Agile development
QlikView Deployment Framework
Summary
12
Sales Perspective
Sales Perspective
Sales perspective data model
Customer stratification.
Customer churn
QlikView extensions and the cycle plot
Governance – design template
Summary
13
Financial Perspective
Financial Perspective
Financial perspective data model
AsOfCalendar
Income statement
Balance sheet
Cash flow statement
Summary
14
Marketing Perspective
Marketing Perspective
Marketing data model
Customer profiling
Summary
15
Working Capital Perspective
Working Capital Perspective
Working capital data model
Rotation and average days
Working capital breakdown
Customer stratification
Summary
16
Operations Perspective
Operations Perspective
Operations data model
On-Time and In-Full
Planning in QlikView with KliqPlan
Summary
17
Human Resources
Human Resources
Human resources data model
Personnel productivity
Personnel productivity breakdown
Personal behavior analysis
Summary
18
Fact Sheets
Fact Sheets
Customer fact sheet consolidated data model
Customer Fact sheet Agile design
Customer Fact sheet advanced components
Customizing the QlikView User Experience
Summary
19
Balanced Scorecard
Balanced Scorecard
The Balanced Scorecard method
The Balanced Scorecard consolidated data model
The Balanced Scorecard information dashboard design
Creating the filter pane bubble
Measuring success with XmR charts
Summary
20
Troubleshooting Analysis
Troubleshooting Analysis
Troubleshooting preparation and resources
Reporting issues
Common QlikView application issues
Summary
21
Mastering Qlik Sense Data Visualization
Mastering Qlik Sense Data Visualization
Qlik Sense and QlikView developers
Visualization extension examples for cross-selling
Plan to master Qlik Sense data visualization
Summary
Index
Index

Using an ETL approach to create QVD data layers

We now know that there are very good reasons for adopting an ETL approach to loading data in QlikView. Now we need to learn how we should go about implementing the approach.

Each part—Extract, Transform, and Load—has its own set of recommendations because each part has a very different function.

Essentially, the approach looks like this:

The approach can be explained as follows:

  1. Extract the data from data sources into QVDs.

  2. Transform the data from the initial QVDs into transformed fact tables and conformed dimensions.

  3. Load the transformed QVDs into the final applications.

The final two layers, the transformed QVDs and the final applications, become potential sources for a user's self-service. We can have confidence that users who load data from these layers will be getting access to clean, governed data.

Creating a StoreAndDrop subroutine

When we are loading data to create QVDs, we will end up calling the Store statement quite frequently. Also, we tend...

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