Hear directly from Qlik employees in our eight unique blogs. Check out the new Architecture Deep Dive Blog!
All about product and Qlik solutions: scripting, data modeling, visual design, extensions, best practices, etc.
Learn about what's new across all of the products in our growing Qlik product portfolio.
Deep dives into specific back-end technologies which allow for the extension of Qlik to fit the needs of the enterprise.
Information on all new product releases, connectors, beta programs, and technical product information.
Updates for Qlik Community offerings, announcements and changes.
Important and useful support information about end-of-product support, new service releases, and general support topics.
This forum was created for professors and students using Qlik within academia.
On this forum you can access and follow the latest updates of our courses and programs with the Qlik Education team.
You may have noticed that we updated the look of Qlik Community over the weekend. This was part of a larger digital presence overhaul to refresh and synchronize our online brand. You will notice that Qlik Community is two words and we have included our logo on the persistent banner. There were no functionality updates so you should not experience any difference performance, loss of content, bookmarks etc.
We hope you like like this updated and fresher visual experience.
Best Regards, The Qlik Community Management Team
Picture this situation: Your company has a long list of products in its catalog, and you want to compare sales per product. Further, the company has recently created a promotional pack with 4 products and you want to see this as one product in your QlikView app. As this is a limited time only situation there’s no need to create a permanent group in your system.
If you ever faced a situation as described above, you will probably already have found several approaches in our community. Most of them will imply a reload process to store the new groups in the backend.
This time Christof Schwarz has created a different method using a combination of the functions PICK () and MATCH () allowing the users to create and administer the grouping on the fly without reload the entire app.
You can find an example and an explanatory video at http://community.qlik.com/docs/DOC-6086
This way to group items is especially well conceived for those situations where users need that flexibly of creating and administering non-persistent groups on the fly, and letting them to check individual items within the group itself.
For those occasions where users’ needs to be able to store new groups to make them available for later analysis sessions and\or dealing with large data sets it still makes sense to go through a different approach that in most of the cases will involve a script process.
ABC analysis is also based in groups, but this time we'll be using three alternate states and Pareto-Select action to solve the ABC customer classification.
Christof’s ABC analysis approach comes with two significant features: It classifies the ABC relatively to the current selection and it stores those classes as is they were normal dimensions until the user recalculate ABC.
Check it out at http://community.qlik.com/docs/DOC-6088
This is a very simple and performant way to implement an A/B/C classification letting users to generate the ABC groups dynamically based on their business needs and to compare those values with other elements in the app.
When you start getting into the Data Visualization field you quickly learn that there are good visualizations and there are bad visualizations. Most scorned are probably the horrible pie chart and its cousin the donut chart. Should we follow Stephen Fews advice and save the pies for dessert or is there a time and place for sub-optimal visualizations?
With data visualization celebrities such as Edward Tufte and Stephen Few being very vocal in their crusade against bad visualizations the rest of the industry has started to follow suit. BI vendors have slowly adopted and almost everyone is promoting data visualization best practices now a days.
I'm not saying they are wrong, a bar chart or line chart for time series are always a better option than one or several pie charts when the core objective is to compare data points.
Sometimes we build QlikView apps for very large audiences, apps they might only use once in a while, apps that aren't critical for them to perform their job and sometimes we build apps that contain downright “boring” data. It’s still an important app; the users would more than likely gain additional insight from the data or the app would help them perform their job more efficiently.
Looking at myself I know there are probably several applications that Qlik has deployed internally that could help me in my job. They aren’t critical for me, I would probably only look at them once a quarter or less but still I don’t open them at all.
These would be apps with “boring” data, apps built according to every best practice in the book. Absolutely no pie/donut charts, muted downplayed color series from http://colorbrewer2.org/ and consisting to 99% of bar charts and data tables. They are in no shape or form bad apps, they are built around solid best practices, every data point is correct and every visualization carefully selected to achieve the maximum efficiency but still I can’t get myself to spend more than 15 seconds in them.
What they are lacking is attention.
I want to make the case that sometimes it’s appropriate to sacrifice a certain degree of accuracy for attention. Sometimes you need some sex and sizzle to get your users to care at all.
For example, humans are naturally drawn to rounded objects versus squared yet our brains are not wired to quickly grasp the sizes of a pie chart. Despite the logical part of my brain telling me that the bar chart would be a more optimum medium to display the information my eyes are still drawn to the pie chart.
The Bar Chart makes it easier to compare the individual values against each other but for me the pie chart is more inviting.
This holds true for pie charts and it also is true for maps. In this day and age as soon as we have an address or a location in our data we are compelled to put it on a map. Why? Most of the time the geospatial dimension is totally irrelevant to our analysis but we still squeeze a map in every application that we can. Because maps engage the users - you can put almost any boring data set on a map and I would still explore it, I will most likely not gain the most knowledge out of the map BUT my interest has been sparked and I might explore the data and the app further.
So should we go wild and crazy, sprinkle every app with pie charts, donut charts, bubble charts or maps?
Absolutely not, while at the same time we need a certain degree of attention to get our users to take interest in the data; we also have a responsibility to represent the data in the most accurate way possible. But what good is the data if people won’t take any interest in it at all?
I say it’s okay to stray from the path of best practice as long as you are aware why you are doing it.
Michael Anthony has previously blogged about Progressive Disclosure which can be used to overcome the initial attention hurdle while the rest of the application can focus on delivering as accurate representation of the data as possible.
TL;DR Pie charts - bad. But sometimes good.
Hi QlikView Portal users,
As part of our drive to improve our customer portal we have now added some new information to the support case view. If your support case is linked to a defect, you can now track the progress of the defect in the portal. Select a single case, and scroll down to find the new "Defect Information" section.
There are four fields with information:
If a bug has the status "Closed - fixed" that means it will most likely be included in the next available Service Release. If the bug is closed during the stabilization phase of a Service Release (i.e. when there is a code freeze/beta just prior to release) the fix will most likely be held over to the following Service Release. We do that to try to minimize code changes during the last phase of the SR release cycle.
Thank you to the Support Operations team for this improvement! Thank you for choosing QlikView.
Global Support Team
We are undertaking a task to review all documents ever posted to the Resources space in QlikCommunity. The goal is to ensure that each document is filed under the appropriate category (or categories) and has meaningful tags assigned to it. Our recent site upgrade allowed us to expand the set of categories, allowing for quicker access to dedicated areas of information. For my sins, I am currently working my way thru the App Development category, so if it suddenly seems like I'm authoring a ton of great material, fear not! I am not usurping your excellent content. Nor have I suddenly been blessed with a ton of amazing insight and information. Its simply reflecting a few updates to categories and tags that I am making to existing content. None of the updates affects the author of each document (or shouldn't if I do it correctly).
As I am going thru this process, I again get to see just how much fantastic content our community members generate on a daily basis. It is truly awe inspiring. The depth and breadth of the materials address such a wide array of topics; it would be impossible to create this material as a single organization. The power of the collective mind is a wonderful thing. I did want to highlight some common elements that are catching my eye (I am equipped with two eyes, but I only use one to catch, while using the other to juggle ... )
1. Please be judicious in the category assignment of 'New to QlikView'. Discussions of variables, macros, $ expansions etc are outside the realm of the typical 'Getting Started' guide. Ensuring that these posts are in the correct categories (e.g. Development, Visualization, Integration) and tagged comprehensively, will ensure that when any newbie is looking for this content that it will be found quite easily.
2. The Resource>Document space is intended for members to share useful content with one another - tips, best practices, approaches to common problems. Its a great place to search if you are looking for an existing document explaining how to solve or approach a particular task. But please refrain from posting questions or problems in the space. Post questions and problems in the appropriate Discussion Forum where other members can offer advice and where you may already find a solution to your problem.
3. Please don't post existing QlikTech content or content belonging to another QlikView member. Release notes, QlikView manuals and blog posts are not appropriate to replicate or post verbatim in the Resource area as Documents. Links to said content are appropriate if these are then discussed in the context of a wider, or perhaps more detailed, thought. E.g. you have found a collection of entries in the Discussion Forums related to Set Analysis, including a link to a solution; curating these into a single document with links to the individual posts and your own content reflecting the original problem and perhaps own experiences or approach is appropriate as a Document in QlikCommunity. Or if you wish to reference a particular section in the QlikView API Guide or a blog post on an QlikTech partner site, but further the conversation with your own thoughts, create a Document with links to the original material followed by your thoughts and insight.
Again thank you for all of the splendid content added to the QlikCommunity Resource site.
Hi QlikView users,
Version 11.20 Service Release 6 (SR6) BETA is now available for interested users to download and test.
There are a number of changes in SR6 including introduction of language support for Korean, Traditional Chinese and Turkish. Our supportability team have also included some changes to email alert templates and also task information summary. Join the BETA program and take a look at the full documentation set for all the BETA information as well as bug fix list. BETA ends 26 March 2014.
Thank you for choosing QlikView and helping us make it the best BI tool out there!
Global Support Team
When released back in October 2012, the QlikView for iOS app introduced offline functionality for the iPad. The app offers a ‘best of both worlds’ experience for QlikView users, allowing full business discovery capabilities when connected, and the ability to access views and maintain associations when offline.
With the release of version 2.0 of the QlikView for iOS app (available in the apple app store), we have made some major improvements in the user interface that are worth noting. While the underlying architecture remains mostly the same, we have added more flexibility and further improved the user experience.
In addition to these major changes, the design has received a major facelift to comply with iOS7 standards, as well as some small improvements such as file details and favorites available on the main screen.
When you use a platform that consists of several services such as QlikView, you need to build trust into the platform to make it secure. The trust will protect the platform from external threats pretending to be part of the QlikView installation to get access to information.
Every time you go from one trust zone to another you need to cross a trust boundary and that means that you need to authenticate. Examples of when you cross trust boundaries in QlikView include going from your computer trust zone to the application using the browser, using the browser to access the administrative interface, loading data from a data source into QlikView, and each time you need to authenticate.
In QlikView, there are two ways to create the internal trust zone between the QlikView Services:
Both of these create trust between the services and hinder unauthorized computers from being able to interact with the QlikView Services, but there are situations where one is better than the other.
You need to protect the communication between the QlikView services from eavesdropping
In this case you should choose certificate trust because that also enables encryption of all traffic between services using SSL/TLS.
You only use Windows infrastructure
Choose Windows Integrated Security as this will be where you have knowledge and it is easiest for you to setup.
All QlikView services do not have access to the Active Directory or you don’t have an Active Directory
Use certificates these will function without a Windows Active Directory.
It is also important to understand that you cannot mix how you create trust in QlikView; either you use Windows Integrated Security or you use Certificates.
When you have chosen the most appropriate way of creating trust, look through the technical requirements found in the Server reference manual before installing to make sure it fits your needs and environment.
To summarize, QlikView has two ways to create trust between services. Both have their benefits; however there are use cases when one is preferred over the other. Which have you used and what benefits have you seen? I would be interested in your comments and questions!
Comparative Analysis is a way to analyze data based on multiple groups. It is not a comparison between two items such as Company A vs Company B. It is all about you, the user, creating customized groups on demand.
For example, you might have seen a graph like this, which is a standard way to compare between companies.
Note: The sketch was created for a demo purpose only.
Comparative analysis lets you group these three companies as portfolio A and compare to another portfolio group B, which may have one company swapped. And then, you may compare which grouping is a better choice for you.
Note: The sketch is created for a demo purpose only.
In this example, I have used the same type of values as two groups; however, you can mix different level of data or different types of data. For example, you may choose one company against an entire industry for business growth comparison, or comparing one country, such as Japan, to a state in the US, California, for population increases. The most common usage of comparative analysis is for basket analysis.
If you would like to try this functionality, go to Financial Stocks Analysis demo > Comparative Analysis tab. Make selections as you’d like and you will see the top chart being populated for your groups.
Here is the video of Comparative Analysis recorded by Michael Anthony.
Bar charts, pie charts, Speedometer gauges, Traffic Light gauges – These are some of the visualization objects that come to the mind when one think’s of designing a Dashboard to show KPIs. Some are used for their grandeur and others simply because they show the data very clearly.
Now, let’s take a step back and rethink on what is the main purpose of Visualization objects within the Dashboard. When there is a large amount of data, it becomes difficult to scan through it in the form of a table and recognize a pattern or select that data which is useful to make sense of situation. This is when visualization objects help the user understand the data clearly in a quick and easy way and enable recognition of the underlying patterns by giving out the big picture and pointing precisely to deviations, outliers and connections.. So, if we take some of the charts that we frequently use in our dashboards and analyze them for their intuitiveness, the answer might not always be positive.
Some visualization objects that have proven to be intuitive in showing the data clearly are sometimes embellished with ornate presentation techniques that compromise the ability of the data visualization to focus on the data itself, while other visualization objects commonly used are not intuitive at all in the first place.
The Speedometer Gauge is a classic example of a visualization object that is used very frequently in Dashboards, the use of which can be arguable. The speedometer Gauge is drawn as a metaphor in the BI industry from the dashboard of a car. In the dashboard of the car, the speedometer does absolute justice in showing the current state. The driver is only required to know the current situation at any given time. Thus, the speedometer solves the main purpose. In a Business Dashboard however, the user more than often times needs to know a whole lot of other things which support the current state like historical trends and other things for purpose of comparison. In which case, the speedometer gauge, which can show only one data point, fails to show the complete picture.
On the other hand, the most simple and extremely popular objects like bar charts and pie charts display the data in a highly intuitive way. They are easy to understand and can inform the user about the patterns and trends. However, if these intuitive charts are not presented well, they can hamper the user’s ability to quickly grasp information and sometimes even mislead the user.
As QlikView application Designers, we are always thinking of ways in which we can represent the data in the most simple and intuitive form for our users. As a result we sought to various resources for references and ideas and often times we come across snazzy looking displays, but it might be of great help to take a step back and analyze whether the representation of the data that we put across is easily understandable by the user or not.
A detailed description with examples of this excerpt can be found in the technical brief here.
Hello QlikCommunity Members,
Several of you have asked about some recent changes in QlikCommunity so we wanted to keep you up to date on a few housekeeping items.
Broken links clean-up
We wanted to let you know that we are in the process of cleaning broken links, old content and areas that need to be refreshed in QlikCommunity. When we migrated to the new platform last year some of the links embedded in old discussion threads did not carry over correctly, resulting in broken links.
Nobody likes broken links- they complicate search results and keep you from getting quick, succinct answers to your questions. Over the next month we will be deleting some of these links and updating others. If you notice one of your posts is now missing a link or it’s been changed please be patient as it’s quite a big undertaking to address these.
We will be refreshing some of the older videos and instructional content over the coming months. Feel free to send a recommendation for content you think should be updated.
In January we successfully blocked a barrage of spammers, but we do have a small set of different spammers trickling into the community. These spammers create an account and send inappropriate private messages to community members. If you have received one of these messages PLEASE send it to us so we can delete the user account. Feel free to forward the spam message directly to me at email@example.com.
As of today- we have deactivated internal messaging in the community to prohibit spammers from sending these messages. We have also stepped up the moderation filters- so if your post doesn’t go live immediately it is probably waiting to be approved. Note that we approve posts throughout the day and will do our best to get them live quickly.
Pre-attentive processing, as the name suggests is the initial stage of processing information by our brain where certain characteristics are immediately detected without focusing on an object. This act is done quickly and effortlessly where the brain tries to recognize certain visual attributes that make things stand out or show groupings of similar objects. Color, shapes, position, orientation, proximity, size and motion are some of the elements that can be easily detected pre-attentively by the human mind. The examples below show how the brain immediately spots anomalies because of their attributes.
While designing a dashboard we rely a lot on showing visual attributes of data for quick and easy detection so pre-attentive processing becomes an important aspect to consider. The ability of the human mind to recognize and process information at light speed can be used advantageously in order to show data outliers and similarities in data in a dashboard.
Applying visual attributes to a dashboard like a bright color or an icon that stands out from the rest of the information can justify the purpose of a dashboard making it easy for a user to gauge the situation at a glance. As shown in the example below, color and icon is used as an attribute to highlight numbers that need attention.
Color is a strong perceptive attribute but there are others that vary in intensity, like difference in shape is not as striking as contrasting colors. Depending on what information needs to be shown, whether qualitative or quantitative, various attributes can be applied.
Visually encoding data for rapid perception can make information consumption in a dashboard extremely easy and convenient for a user. And since a dashboard is a summary or high-level information providing system, it is important to strive to be as visually informative as possible to target the pre-attentive senses in a user.
So, the use of pre-attentive information processing techniques while designing dashboards can not only justify the purpose of the dashboard but also help in projecting information as needed.
The AGGR Function.....
I thought I would start this blog post with a simple multiple choice question:
a - Used in many QlikView applications to great effect
b - Mis-used in many QlikView applications
c - Used to return an answer without really knowing why you get the answer
d - Not used at all because we're "not quite sure what is does"
e - All of the above
The answer in my opinion is "e - All of the above".
When I came to write this post and indeed the technical brief, the hardest part of all was actually coming up with a really good, easy to understand description of AGGR, as it has to make sense to both "technical" and "not so technical" people. I finally settled on the one below...
When it is used, the AGGR function produces a virtual table, with one expression and grouped by one or more dimensions. The contents / result of this virtual table can then be used / aggregated by a further outer aggregation function(s).
With this definition in mind, I have produced a Technical Brief and application which can be found here and here. In this document I have tried to provide an overview of the function and provided some examples of where it can be used to great effect.
So, when should you use AGGR? The answer is: Whenever you want to perform an aggregation in two steps. In the technical brief we show you some scenarios like.....
I would also be interested in any other creative and powerful uses of AGGR you may have.
Who you are is the product of all of the experiences you have had, and not had, throughout your lifetime. Nobody operates in complete isolation. Everyone is influenced by sources outside of themselves. We take those experiences and internalize them with our other memories in our own way but ultimately everything you come in contact with serves as material for the future you. So it stands to reason that new ideas & creativity are also the result of taking existing ideas and transforming them.
People frequently talk about ideas/people as being "totally original," but the truth is that originality is rather unoriginal. People with seemingly totally new ideas are really just the result of taking existing concepts and bringing them together in new ways. Perhaps you can identify the original source material, perhaps you can not, but everyone is influenced by ideas outside of themselves and nobody creates something entirely new.
The 4 part video series Everything is a Remix is a fantastic exploration of this in action. From music, to film, to mechanical invention everyone is influenced by the work of others.
I have received a few emails from QlikView developers asking what the best practice is for placing list boxes. There are two arguments that you may think of right away.
In information design, left-side, top-left to be precise, is always used for the most important information. It is because as a human-nature that’s the space people pay attention to first. So why should I waste the space for placing the navigation pane there? I should place it on the right.
Another argument is that people are used to use left navigation because most of the web sites have menus on the left. Think about a shopping web site. All departments, categories, genders, sizes… whatever you think of usually on the left hand side. So why should I go against human’s habit and place it on the right-side? People will get confused.
I can buy both arguments. But then how about placing it at the top? I have seen QlikView applications that have navigation pane at the top. Is this the best of all? Let’s think about this in QlikView usability, with an elimination method.
That being said, I personally think that having the left-side pane works the best in QlikView applications, and here are the benefits.
Lastly, you may wonder why I have the timeline list box at the top. This is my 11-year QlikView habit. I believe it is the best to keep the timeline list boxes separated from other selection categories.
If you cannot give up the top-pane option or wish to have many list boxes on user’s figure tip, then you can use a trick. Here is an example. When you click on the ‘filter’ button, then there is a drop panel with list boxes. I recommend you using this in dashboard where you need lots of real-estate for important information. Or also you can use this together with the left-pane navigation. In this case, create list boxes for the most frequently used fields on the left for easy navigation (accessibility), and you can create the hidden panel for additional list boxes.
Now it is up to you what method you will use in your QlikView application. Will you go with a top, left, right or hidden pane?
You can also download the technical paper on this topic here.
QlikView version 11.20 SR5 is now available. This important release includes Direct Discovery enhancements, amongst other new supported platforms and capabilities. It can be downloaded here.
Direct Discovery broadens the classic in-memory capabilities of QlikView to allow for direct query access to Big Data solutions like Hive & Cloudera Impala as well as traditional data warehousing solutions like Teradata and SAP HANA.
11.20 SR5 also includes some additional enhancements, see below:
- Enhanced Direct Discovery capabilities - major re-write and new functionality has been added
o Possibility to use WHERE clause
o Cancel query
o Global search on dimension fields
- Map Extension - a new mapping extension delivered together with an updated Extension example QlikView application
- SharePoint 2013 Support - a new proxy that can be used for SharePoint integration, delivered in the Workbench installation package
- Added support for QlikView Desktop on Windows 8.1
- Added support for IE11
The Products Team