Common Sense for Qlik Sense

Common sense for Qlik Sense

The Qlik Sense platform has been around for quite some time, and with every passing year, the tool has evolved to suit the needs of not only novice data analysts but also the advanced data gurus. It's easy and fun to develop and has a clean and edgy UI. Moreover, the charts are as pleasing as they are user-friendly. We often struggle to create the perfect charts that are straightforward enough to express the embodied data correctly. Sometimes it's a bit too tempting to try out the various presentation options available to create a chart which causes the data to go off-track.

Let’s look at some examples of how we can use common sense to optimize these charts and make them more intuitive.

1. Legends

Observe the chart on the left. It contains a lot of information, but wait! Isn’t there some critical information missing? Yes, the legend which is the most crucial piece of this chart and tells us what this data is about is missing. While quite apparent don’t forget to display the chart legends where applicable or else the chart will hold no meaning.

Also, for charts with legends, it’s already daunting for the eyes to go back and forth from chart to legend to make sense of what is what. If the legend is jumbled, it can be even more troublesome when the sequence of colors in the chart and the legend are different. Below, compare the chart on the left vs. the one on the right.

The chart on the right is more intuitive since the chart and the legend are coordinated. It’s always a good idea to follow the same sequence of colors for the legend as that of the bars to maintain visual consistency and make it quick and easy to grasp the information.

2. Colors

Color can hold an important piece of information when it comes to charts. Therefore, using colors mindfully is key to an intuitive chart. In the example below, the green color is used to visually signify the teams that have surpassed targets, which gives additional visual information apart from the length of the bars.

At the same time, just like this example, you may consider avoiding the color red for the other bars even if they have not reached the target yet. This is to potentially motivate or encourage the remaining elements such as sales reps. Also, this applies to when goals are not set for such as YTD but for the entire year. Seeing red bars at the beginning of the year is purposeless.

Let’s take a look at the chart below on the left. Colors are unnecessary since the length of the bars itself tells us about the most profitable shared products. Just because there is an option to do so, using colors which hold no significant meaning should be avoided to maintain the balance of the chart. The chart on the right can easily be interchanged by the one on the left which gives a clear idea of the information and focuses more on the length of the bars rather than colors.

On the other hand, using colors to define a metric within the chart is a robust method of encoding data. In the example below the treemap image 1 show sales of products by reps. It’s easy enough to see which product was sold the most by each rep based on the size of the rectangles. Whereas in image 2, color is used to define the discount %, and immediately you see the reddest spot and notice that Tom is offering the highest discount in the product category of swimwear. This way you can locate the outlier quickly.


Below are three variations of the original blue chart and take a look at the chart at the bottom left. Because the color represents each product category, not only can we quickly identify the product that has the largest box but you can also spot which product comes 1st, 2nd, and 3rd, by its color. You can tell that the light blue box which is Men’s Clothes is not among the top selling products for all reps but Rob. You can’t see this on the other three charts without reading the labels.

Using colors in charts where it can aid in either showing trends or outliers can help in reading the charts more quickly and efficiently, hence making charts more intuitive.

3. Sorting

Sorting the data by y-value may seem very straightforward and an obvious thing to do but it sometimes gets overlooked and causes the chart to be unintuitive and misleading like the chart on the left. The same chart on the right is sorted by y-value which is visually more informative because now you can quickly see that more than half of the employees are account managers and storemen, an insight that can’t easily be detected with the chart on the left.

4. Data Quantity

Observe the charts below. On the chart on the left, it’s just impossible to differentiate between the sizes of all the pie slices and tell which color goes with which slice. A good idea would be to group the smaller slices in a single category called others and optimize the quantity of data shown within the chart to make the chart visually comprehensive.

Common sense along with little tweaks can go a long way to make charts intuitive and visually informative. These considerations may seem trivial at the time of development but if not done right can hamper the way in which data is processed by the human mind causing the downfall of the design. Checking if you have legends where applicable, applying colors mindfully and intentionally, creating meaningful sorting for data and making sure data is quantified in the right way. These are simple yet compelling reasons to make charts more intuitive and in turn make your Qlik Sense application most insightful just by using common sense.

To find out about Infozone’s expertise in Qlik Sense contact us today!

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