Qonnections 2017 in Review

Another Qonnections is in the books.  Like all Qonnections (this is my 5th), it has passed like a whirlwind of activity and fun. I will try to sort through the experience to find some of the random notables coming out of Qonnections 2017.

Product News

The Fisheye was one of the clip-on camera lens provided in our “swag bag” this year. Very cool.

The most exciting information came out of the day 1 general session. Anthony Deighton revealed the 2020 Vision and Roadmap. The overall vision is that unlike the “scary version” of AI where the machines take over the world, Qlik is embracing AI as “Augmented Intelligence” where the human is still the central point in the decision-making process and the machine intelligence supports the human in an intelligent way. As a result, Qlik declared they are “investing heavily” in AI related technology.

With this overall vision, there were some major areas of focus and new features looking to become part of Qlik Sense (in no particular order)

  • Improvement of the Data Manager (self-service loading and transforming of data)
  • New Visualizations – Boxplot, Histograms, Distribution Chart
  • Integration with R and Python (and other tools to be announced)
  • Dimensional Color Intelligence
  • Context based Search and learning
  • Qlik Sense App for fully featured Offline Use
  • Improved On-Demand App Generation
  • Certification process for externally created extensions
  • Focus on a hybrid cloud environment where clients have a seamless mix of on premises and cloud based solutions.
  • Big Data Associative Indexing

The most interesting news for me is the idea of Big Data Associative Indexing. Although I am foggy on the details, it seems that we will soon be able to spread the associative engine load for an app across more than one node. Unlike the “Direct Discovery” feature that was touted as the answer for Big Data (it was not), Big Data Associative Indexing represents a breakthrough in the core technology and a REAL SOLUTION for big data. This will absolutely bring the power Qlik to much larger data sets. I cannot wait to learn more about this.

Where was QlikView?

This is admittedly a horrible picture. Maybe you can make out the one mention of QlikView on this slide.

Which of these features will make it into QlikView? We have absolutely no idea.

Although of course we expect Qlik Sense to remain center stage, there was nary a mention of QlikView in any content that I saw the entire conference. I did see that QlikView is part of the roadmap, with 1 release in November.

I understand the more sustainable path for the future more directly involves Qlik Sense. With that said, the large bulk of Qlik’s customers are still using QlikView. And anecdotally, some of the customers I spoke with at Qonnections voiced disappointment about the lack of attention for the product they use and love.

Although Qlik has made the claim that they are “officially supporting and improving both products well into the future”, it is clear to me that what Qlik really wants is for all customers to move to Qlik Sense as soon as possible.

General Notes

The Luminary Cocktail Event

The Luminary event was great fun. I was a little overwhelmed meeting so many legendary people at one time. So, I apologize if I said anything weird out of my obvious nervousness. Special Shout-outs to Brian Booden, Karl Pover, Julian Villafuerte, Angelika Klidas, Jason Michaelides, Richard Pearce and Gysbert Wassenaar.

The Keynote Speaker Jason Silva

Well, I don’t want to hate on Jason Silva too much. He seems like a really nice person. But it felt like he read some Carl Sagan and then used a word cloud of the top trending words about the “future” to cobble together his speech about “moments of awe”.  It seems his passion is genuine, but the feeling of awe he was obviously experiencing was not transferring to me.

Maybe I feel this way because he followed Scott Kelly, the keynote speaker from last year. Commander Scott Kelly is an American astronaut who had just completed a 1-year mission in space. In contrast to Mr. Silva’s emotive style, Commander Kelly was calm and matter-of-fact in his presentation. Yet last year I found myself at the edge of my seat clinging to his every word. That was an example of a truly awe-inspiring moment for me.

Breakout Sessions

I am only speaking for myself, a developer who goes down the technical track of the breakout sessions. It seems to me that there were fewer opportunities for real learning and knowledge transfer this year than in past years. One notable exception was the hands-on workshop provided for GeoAnalytics. That is the kind of learning that helps me in my business.

Final Thoughts

I firmly believe that Qlik Sense and QlikView are amazing products. Qlik is undoubtedly the leader of the Business Discovery space.

With that said, I think there is a slight disconnect developing between Qlik and their partners and customers. My hope is that the Qlik team does not take partners and customers for granted. Listen to the partners (all the partners). Listen to the customers (including QlikView customers). They will happily tell you the pains they are having with the programs and the products.

All-in-all, Qonnections 2017 was a successful event. Personally, I always get so much out of Qonnections. The highlight for me this year was meeting so many great new people.

Happy Qliking!


Show Off Your Favorite Qlik Dashboard

Many Qlik Developers I meet have really awesome Qlik dashboards they have created. The dashboards I have created are like my little offspring. Some are ugly, yet functional. Some are super-colorful POC demos that never see real use. And some are that happy balance of intriguing visualization combined with useful insight.

This is an opportunity for you to be a part of LivingQlik. To participate, just find your favorite QlikView or Qlik Sense dashboard sheet that YOU have designed. Then upload it using the form below. It can be a fun application, or extremely useful or incredibly unique or visually beautiful or all of the above.

In 2 weeks, we will have a follow-up post featuring some of the more interesting examples. We will credit you (if you wish) and offer some comments on what makes each one special.

How can you participate?

  • Use the form below to upload your file. The screenshot needs to be either a png or jpg and must be less than 10mb.
  • Feel free to enter your name or you can simply type “Anonymous” if you do not want to be credited.
  • You can type or paste in some commentary that directs our readers to the interesting or unique part of the dashboard. If you don’t enter anything here, I will add my own “editorial” which might not match your intention.
  • Please only upload public data or data you have permission to upload.
  • By uploading an image, you are giving LivingQlik the right to publish the image and the accompanying name and text you entered.
  • Your image might be cropped and or resized to meet aesthetic guidelines.
  • Space is limited and inclusion or exclusion from the post is no indication of the quality of your work. 🙂


Send LivingQlik Your Screenshot Now


Here are a few examples I created. I am sure that your example will blow me out of the water.


This is one of the sheets from the Internet of Things app featured in a prior post. The use of red is aesthetically pleasing even if the distances between the individual colors are too small to be effective. I rarely use radar charts, but this one sure does look cool.


This is a QlikView example that I have used to monitor my exercise. The colors are persistent so that Running is always blue, for example. I got the idea to put an icon inside the donut chart from another dashboard I came across. Although I am no longer this serious about analyzing my workouts, this was fun for a while and highly functional. This app was featured in this article that described how to assign the colors at multiple levels.


This was just a fun app that utilized a dataset regarding UFO sightings. It uses the Simple Table extension and the CapVentis Zoomable Circle Packing extension. Both can be found on Qlik Branch.


Final Thoughts

Be sure to come back in a few weeks to check out the results.

Thank you in advance for contributing your beautiful work to LivingQlik. You are what make this community great.

Happy Qliking!



LivingQlik Roots: How-To Create Cyclic and Drill-Down Grouped Dimensions

Featured Image - Cyclic and Drill-Down Grouped Dimensions

Today, I will cover some basics on how to create dimension groups for your QlikView applications. I will also talk about using GetCurrentField to make your charts behave more seamlessly with your groups. This info is must-have for any serious QlikView developer.

What are Grouped Dimensions?

When you build a chart, you typically will use at least one dimension field so that the aggregation in your expression gets calculated for each value in your dimension list. This is a simple concept that we can expand on.

Grouped Dimensions allow the user to “switch out” the dimension with another field. This allows us to re-use the screen “real-estate” without having to create a separate chart for every needed dimension.

Grouped dimensions can be used in any chart. I also use them sometimes in listboxes. They save space if the users understand how they function.

Cyclic vs. Drill-Down Dimensions

In QlikView, grouped dimensions come in two flavors.

Cyclic Dimension – Allows user to choose the dimension at will.

Drill-Down – When a user makes selections resulting in one possible value, the dimension changes to the next dimension field.

The key thing to remember here is that users directly control the dimension in the cyclic style, while the selections drive the displayed dimension in the drill-down style.

Creating a Cyclic Dimension Group

You should know that when you create a dimension group, it can be used in any QlikView object within your application. With that said, they can be either created within your Document Properties or directly in a chart. Go to Settings –> Document Properties –> Groups and select New

Create a group name, choose the radio button for Cyclic Group and then add the fields you want in your group. Note that the order of these fields will represent the order in which users can normally switch between them with the top field being default.

You can also change the label for each field. Simply click on the field and enter a new value in the label field. In this group I renamed my field MonthYear_Short to Month.

Now create a chart using your new cycle group as a dimension. You will see grouped fields at the very top of the dimensions tab.  Once your chart is created, the user can click directly on the yellow circle or can use the pull down to select the desired dimension. Super Cool!

Creating a Drill-Down Dimension Group

Now let’s create a drill-down dimension. This time we will build the group from the chart. Create a line chart and when you get to the dimensions tab, you can select Groups in the bottom left.

Name your group and select the Drill-down radio button. Note that the fields I add are in a specific order from summary level to detail. The fields must be in a hierarchy because of the way the drill-down field operates.

Utilize the new drill-down group as your chart dimension and finish creating your chart. Note that clicking the arrow does nothing at the highest level. Instead, make a single selection in your chart and you will see the dimension change to the next level. At that point you could click the arrow which serves to undo that selection. As you make selections in these fields or other fields that result in only one possible value, your chart will automatically display the next detail level.

Which Group Type is Better?

I am often asked which style is better and my answer is always “it depends on your audience”. Most sophisticated users will prefer a cyclic group because they can directly control the dimension being displayed regardless of the selections.

Users who “just need the dashboard to work” will probably prefer the drill-down groups as they don’t have to do anything to the chart to make it drill down to the next level.

With that said, I have had situations where the client wanted the same chart done both ways.

Professional Tip – Sorting

You might run into a situation where a field in your group is not sorting correctly when in use. Take the example below where we have used Quarter Year. Sorting this alphabetically is wrong and numerically does not work either. Either way, we cannot determine the sort from our normal chart Sort tab.

Open the group and go to Sort Orders. There you can select the field and assign the sort of your choice. In this case we are sorting by expression using a counter field that was added to the data model for this purpose.

This is Where GetCurrentField Comes In

Sometimes, an expression you create needs to interact with the fields you are using for dimensions. This is typical for expressions with aggr functions. So what do you do when your dimension can change? Well, of course, there is a function for that. Let’s cover a few applications of GetCurrentField.

One great application of GetCurrentField is to provide some clarity regarding the dimension currently in use for the chart. I like to modify the title of the chart so it displays the field that is currently being used. As the user cycles or drills though the dimensions, the title of the chart changes to match.

This expression could be entered in the General tab for Window Title.

Resulting in a dynamic title that changes with the drill down.

In another use-case, we have created a line chart that measures profit over time. And instead of using a static dimension like date, I instead created a cyclic group that allowed the user to cycle from Year, to Month, to Date. This is a very common requirement. But in addition, the users require a reference line 75% to the maximum value of the chart and also at the 25% point. This would be pretty simple but how do we know what the highest value is as we cycle from one dimension to another.

Reference lines are created in the presentation tab. Notice that I had to put the GetCurrentField function in dollar-sign-expansion.

Note: If GetCurrentField is not working try putting it in dollar sign expansion

I created both lines and here is the final chart. As I click the cycle button, the reference lines recalculate to the new maximum value.

Final Thoughts

Please note that Qlik Sense does offer some concept of grouping fields but operates a bit differently. And to-date, GetCurrentField is NOT a supported function.

Here is some interesting further reading on the GetCurrentField function.

More Reading –

QlikView Maven – Expression Knows Which Cycle Group Field is Active

Quick Intelligence – QlikView Caption Contest

QlikShare – System/Meta Data Functions in QlikView – Part 1

Happy Qliking!


The 9 Worst Data Visualizations Ever Created

Every year, the worst movies of the year coming out of Hollywood are “honored” with an award called the Razzie. In an industry that normally pats itself on the back at every turn, the Razzies are a nice way to recognize that not every film churned out of the Hollywood machine is worthy of praise.

In similar fashion, I thought it would be fun to award some of the worst data visualizations coming out of our collective BI industry. Although it is always fun to poke fun at data visualizations that might be lacking in usefulness, it is also an opportunity for us to learn so that we do not make the same mistakes in our own work.

Not Using Dimension Limits

This was an amazingly inept example I came across. This pie chart actually breaks a few rules.

First, a pie chart is supposed to show relationship of each slice to a whole. Sampling only the 100 most active tweeters and making that the whole in this case does not really give us real value. A simple bar chart would have been a fairer representation.

Secondly, and more obviously, how does representing all 100 slices help us? We certainly cannot see all 100 names in the legend on the right, not can we detect the differences between the slice sizes as we progress along the slices.

3D Pie Charts

Speaking of pie charts, here is another one that definitely “chaps my hide”. This pie chart is already bad just because it is in 3D. Tilting the pie to give it a 3D appearance distorts the slices, making it harder to detect how large the slices are relative to each other and to the whole.

Add to that, the slices have a high degree of transparency to make it even more difficult to see where a slice begins and ends as the colors bleed together through the depth of the chart.

Not to pile-on, but the developer also neglected to sort the slices in descending order by the metric, making this even harder to read.

Speaking of reading, forget about figuring out which label goes with which slice. It is not possible to follow the little lines to get to the correct label. Ouch…

Alternative Facts

I couldn’t resist adding this one. It only has 3 slices which surprisingly add up 193%.

3D Bubble Chart

I can admire this developer’s ingenuity. “If only the scatter plot could handle one more expression”. Making the chart 3D indeed adds another axis the developer calls the S-axis. But trying to make sense of this takes a whole lot of effort from the reader.

Also, because the chart is presented in 3 (oh wait, 4) dimensions, it is difficult to decipher if a sphere is larger because it is close to us on the Z-axis or if it is just larger, corresponding the S-axis.

Line Chart on a Non-Continuous Axis

The chart below is an example of using the wrong chart type for a data visualization. This data would have better been presented with a bar chart.

Line charts are meant to display an expression against a dimension list that is continuous, where the values relate to each other in a specific order. I generally think of a date sequence like months or years.

The card games presented here could be in any order. There is no reason to connect the points with a line.

The 3D Bar Chart

I have a special hatred for the 3D bar chart. Firstly, by nature of the chart being drawn in 3 dimensions, it is difficult to follow the height of each bar to the correct Y-value. This becomes more difficult as we get away from the axis.

But the more serious crime is that I can’t even see some of the values for the rear dimensions as they are hidden by the bars of the values in front of them. I guess those data points were not important.

The Tip of the Iceberg

Speaking of Fox News, here is another winner. This time we are looking at a bar chart representing people who have enrolled in United States government sponsored healthcare. If you do not inspect the numbers (which were thankfully printed on the chart) the bar on the right appears to pass the bar on left 3-fold. But if you take the numbers into account, it becomes more obvious that there is something wrong here. There should only be about a 15% difference from one bar to the other. Why is the visual so far off?

Well we don’t really know, but my assumption is that the creator of this chart decided to start the Y-axis at a number other than zero. We don’t really know where the Y-axis really starts here because there are no numbers on the axis. This is a very misleading chart.

The Dreaded Infographic

Hold on to your seats. This one is really bad. In this infographic of “How Baby Boomers Describe Themselves”, there are so many problems, that I don’t know where to begin.

Let’s start off by saying that the percentages given do not add up to 100%. Does this mean that the data was incorrectly calculated? Or does it mean that each person was allowed to describe themselves with more than one trait? We will never know.

Also, no matter how you look at the color areas of the chart, the area or vertical space of the colors does not seem to correspond with the numbers presented on the right.

Having the colors filling up the shape of a person does not help the situation. Because a novel shape will have varying widths from bottom to top. This makes it very hard to know what percentage each color represents.

Finally, what is the value for this particular data set of having the shape be a walking person?

As a general rule, maybe we shouldn’t use a strange shape to represent these values. It only serves to confuse and obscure the story the data is trying to tell.

The Worst of the Worst

So what is worse than using an obscure shape to represent your values? I would submit that using a visual shape that is in itself, a whole other kind of chart would be worse.

At first blush, this data appears to be related to the 50 United States. But the data actually has nothing to do with geographical analysis. The reader is supposed to read the chart from left to right as the west coast corresponding to the year 1960 and time moving forward to the east coast which represents 2060.

The second problem with this chart is that none of the percentage seem to add up to 100%. For the left and right extremes we can maybe assume that the numbers for the upper regions are simply too small to be displayed. But how do we explain the middle section? There are only three colors and the three numbers add up to 92%.

This chart should be a stacked line chart. That way we could clearly see the important parts of the chart where the lines experience real movement. Ironically, what could be the most important part of the chart (the great lakes area in the northeast) is completely missing.

Final Thoughts

The mistakes in these date visualizations are obvious and extreme. But after you point your finger and chuckle, take a step back and look at your own visualizations. I know I have made some of these mistakes on a smaller scale.

Happy Qliking!

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