In chapter 4 of Learning QlikView Data Visualization, I explain how to perform multivariate analysis with heat maps and mini-charts. However, I left out the possibility of using a parallel coordinates chart to analyze the relationship between several variables. Honestly, this method is rarely great for communicating your discoveries to others, as Stephen Few explains so well in his white paper “Multivariate Analysis Using Parallel Coordinates“, but it can be a great tool for data discovery and analysis.
Parallel coordinates chart with qualitative values
A parallel coordinates chart is commonly used to link common attributes of the dimension. For example, it could show us the most common characteristics of a customer (i.e. age group, gender, marital status, etc.) We will create this type of parallel coordinates chart in a later post.
Continue reading “KPI Parallel Coordinates Chart”
Many times users lose a great opportunity to use color to make their QlikView interface more appealing and insightful when they choose to make a rainbow-colored bar chart. One of the most important subjects I had to leave out of Learning QlikView Data Visualization was how to apply the coloring technique of a heat map to a bar chart. In the book, I left the exercise of combining these two data visualization techniques to the reader. In this blog, let’s review how we combine the two by adding data about the profit generated from each customer to a simple bar chart that ranks customers by their net sales. If you want to follow along with the exercise below, download Sales_Project_Analysis_Sandbox.qvw. Before starting the exercise, let’s review what colors we want to use to represent data in a heat map. Colorbrewer is a great site to choose color-blind safe colors schemes that are either sequential or diverging.
- Sequential color scheme – The greater the data value, the darker the shade of one color.
- Diverging color scheme – The combination of two sequential schemes that are divided at some center point (e.g. zero). The greater the distance from the center point, the darker the shade of either of the two colors.
Since we will be adding data about profit which can either be positive or negative, we use the diverging color scheme. Also, we choose orange and blue as the two colors that make up the color scheme in order to ensure the involvement of those of us who are color blind. I’ll assume we’ve already created a simple bar chart that shows the top-selling customers based on net sales like the one pictured below.
In the properties window of our bar chart, let’s perform the following steps.
- In the Expressions tab, click the plus sign next to the expression to expand its properties.
- Select Background Color and click … in the Definition text area to the right.
- In the File menu of the Edit Expression window, select Colormix Wizard…
- Click Next >.
- In the Value Expression text box, type Sum ([Profit Margin]) and click Next >.
- In the Upper Limit section, click the green color button twice and then in the Color window select blue (Red=0, Green=128, Blue=255).
- Select the Intermediate checkbox and type 0 in the text box below.
- In the Intermediate section, click the yellow color button twice and then in the Color window select light gray (Red=192, Green=192, Blue=192)
- In the Lower Limit section, click the red color button twice and then in the Color window select orange (Red=255, Green=128, Blue=64)
- Click Next >.
- Clear the Enhanced Colors checkbox to make extreme values stand out.
- Click Finish.
After adding adequate labeling and accepting the changes made in the chart properties window, we now have the following chart that is both appealing and insightful.
Here’s the video tutorial.
Hope to see you around, Karl
If you have the QlikView Personal Edition (PE), you can only open QlikView documents created locally on your own computer. So, if you are downloading and installing QlikView for the first time, or you don’t have a full QlikView license and are using the QlikView PE, you are going to get the following error when opening up the QlikView files (QVW) included with Learning QlikView Data Visualization.
Click Abort, and perform the following steps before starting the exercises included in the book.
Continue reading “How to do the exercises in Learning QlikView Data Visualization without a QlikView license”
After various QlikView books intended for QlikView developers, I’ve recently written a book that is aimed to help all those business users that suffer middle children syndrome. In almost every one of my customers, I’ve worked with a group of QlikView users that don’t want the responsabiity to write the scripts that extract and manipulate data, but aren’t spoiled enough to have each chart they need created instantly by a team of developers. Instead, they use existing data models to create their own analysis at the pace of changing business needs.
Learning QlikView Data Visualization comes out this week and is intended to help this group of users.
Back In March, Packt Publishing offered me the challenge to teach readers in a little over a hundred pages the basics of QlikView data visualization. The result is a fast-paced, no-nonsense book that explains by example. Rather than focus on each chart type and checkbox available in QlikView, I focus on how to best implement a set of common analytical techniques in QlikView.
Continue reading “Learning QlikView Data Visualization – Expected this week!”
My name is Karl Pover and I would like to welcome you to my website. I’ve been a data discovery consultant since 2006 and the goal of this blog is to organize and share my thoughts, experiences and expectations within the realm of data discovery.
I’m originally from the small town of Farley, Iowa and currently live in one of the largest cities in the world, Mexico City. This blog is my chance every couple weeks to take a break from the fast-paced city and ruminate over better practices and methods for a successful data discovery experience while reviewing different data discovery software and tools.
Please consider that the data discovery tool I use most is QlikView, but I am open-minded.
Last, but not least, if you require data discovery consulting services, please visit evolcon.com or e-mail me at firstname.lastname@example.org.