Unlock a world of possibilities! Login now and discover the exclusive benefits awaiting you.
This space offers a variety of blogs, all written by Qlik employees. Product and non product related.
By reading the Product Innovation blog, you will learn about what's new across all of the products in our growing Qlik product portfolio.
The Support Updates blog delivers important and useful Qlik Support information about end-of-product support, new service releases, and general support topics.
This blog was created for professors and students using Qlik within academia.
Hear it from your Community Managers! The Community News blog provides updates about the Qlik Community Platform and other news and important announcements.
The Qlik Digest is your essential monthly low-down of the need-to-know product updates, events, and resources from Qlik.
The Qlik Education blog provides information about the latest updates of our courses and programs with the Qlik Education team.
Hello Qlik Users,
Happy Qlik Sense Patch Wednesday!
We have two new Qlik Sense patches available on the Qlik download site:
Qlik Sense Patch | |
November 2019 Patch 12 | |
June 2020 Patch 1 |
As with all software, please follow best practices when upgrading by backing up your Qlik Sense environment and testing the patch in a QA environment first. For more guidance on upgrade, see the Qlik Sense Upgrade guide. This guide was put together by the Qlik Digital Support team and offers step-by-step instructions, pictures and troubleshooting tips.
Be sure to subscribe to the Qlik Support Updates Blog by clicking the green Subscribe button to stay up-to-date with the latest releases. Please give this post a like if you found it helpful! Also, please let us know if you have any questions or leave your feedback in the comments.
Thank you for choosing Qlik!
Kind Regards,
Qlik Global Support
Hello Qlik Users,
It’s rare we blog twice in the same day but we wanted to make you aware of an issue that has been found in Qlik Compose for Data Warehouse.
The issue may affect customers using Snowflake, Replicate CDC and type 1 entities.
The following versions of Qlik Compose for Data Warehouse are affected:
The fix for the issue is now available on the download site and is version April 2020 SR2 (6.6 SP04). It is recommended to update to April 2020 SR2 as soon as possible. As with all software, please follow best practices when upgrade and refer to the user guide for instructions on upgrading.
For more information on the issue, please see CDC task data inconsistency for Compose Data Warehouse April 2020 Release and SR1.
Be sure to subscribe to the Qlik Support Updates Blog by clicking the green Subscribe button to stay up-to-date with the latest releases. Please give this post a like if you found it helpful! Also, please let us know if you have any questions or leave your feedback in the comments.
Thank you for choosing Qlik!
Kind Regards,
Qlik Global Support
Ng Ying Xue (YX) is the challenge five winner of our first ever global Qlik Academic Program Datathon. She is an Accountancy and Business Analytics student at Nanyang Technological University, Singapore. In the early years of her university life, YX gained interest in analytics and that’s how her journey began. This further led to her active involvement in her school’s Business Analytics Club while taking up the role of the Club’s president in her senior year.
It was as during her time in the Club that her interest began in data visualization. As a new analytics student at that time, YX was rather fascinated with the capabilities of data visualization software, which she says, “allows self-service analytics for anyone, especially for individuals without a technical background.”
YX first tried Qlik during her analytics internship and was rather amazed at all the features it possessed. She found the interface easy to navigate, and she worked on a small project using Qlik. During the internship, she also did some research and learned about the Qlik Academic Program. She signed up for the program and immediately started taking the training courses offered by Qlik. YX was impressed at how customizable the software could be and the extensive extensions available. However, she felt there were few opportunities to apply the skills she had learned and to present use of the software outside of the few data visualization projects she had during her internship.
Opportunity came knocking when early this year, YX’s Professor shared an email regarding the Academic Program Datathon Qlik had organised. She was motivated by the idea of being able to apply her data visualization skills to create a data-driven solution towards a resilient climate and planet. YX thought this was also a good avenue to apply what she had learned, and to showcase how data could be applied to solve problems using Qlik. However, since she did not have much experience with Qlik, she struggled a bit initially. YX found inspirations from some examples on the Qlik demos site and made full use of the forums to get answers to questions regarding the features or extensions she wanted to implement in her application.
YX says, “Since there are limited opportunities for students like myself to apply our skillsets to the real-world context, I am extremely grateful to Qlik for organizing this Datathon. Through my participation in the Datathon, I was able to reaffirm my passion for analytics and problem solving. Moving forward, I am looking to continuously improve my skillsets and make a change using the power of data.”
Register now to watch YX and the other Datathon challenge winners present their amazing solutions during QlikWorld Online. Don’t forget to vote for your favorite solution and help Qlik award the overall winner of the Datathon!
A few months ago I stumbled upon a fantastic app that showcase the not very well known math functions in Qlik. The app does a great work popularizing math & statistics using default Qlik functions. Ever since I put my hands on the app I wanted to blog about it.
I asked the app's author, Mária Šándorová @JaMajka1 to introduce the app:
I started to develop the app like this the same year I started to work as a full-time Qlik developer. For me it was a good way how to explore mathematical possibilities together with script and expressions syntax of a great tool that was new to me. After that it didn’t have my focus for some time. And then there was a boom of advanced analytics and predictions. Qlik community, different blogs, even my own presentations and Qonnections were full of SSE – possibilities how to utilize mathematical power of R or python for these algorithms.
They are great tools with their advantages in more complex algorithms and a good step forward for Qlik that it can be integrated with them. However, I think that because of all these information and materials about advanced analytics for Qlik in R or Python or anywhere else, we started to underestimate Qlik’s own capabilities.
When someone needs to calculate a correlation, identify outliers, run k-means clustering or test data normality, we really don’t need to use an external tool – we can use Qlik’s default functions as are or script an algorithm within Qlik. I spent days building this app and I still haven’t covered many areas like hypothesis testing or linear regression. Not to mention algorithms you can script within Qlik. So there really are many advanced analytics and statistics possibilities integrated within Qlik itself, too.
I think it’s amazing that we have different options on how and where to calculate something! And I believe that for being able to make a good choice, we need to consider our options and the first step is to know we have it 😊.
So, exploring Qlik’s capabilities in statistics was the first reason to create this app. It defines the content of it. The structure and design of the app is driven by something different. I really like data literacy initiatives and I believe we need to help people become data intelligent and understand their data.
I know, this app is more about mathematics than about context and visualizations, but I think it’s also an integral part of the data intelligent company – even if not necessary important for all users. And what is a better way how to understand the function if not having a simple use case and a generated dataset in an interactive tool?
I love the idea of trying possibilities and seeing the results in the same second. In advanced sections of the app you can select a subset of data in two clicks and thanks to Qlik, everything is recalculated! Select outliers only and see the results of mean and variance … select excluded values and see their results… That’s brilliant for understanding what’s going on!
And if you prefer specific formulas and definitions, they are there, as well 😉.
I hope you like it as much as I do
Hello Qlik Users!
June brings new releases for:
Here are some of the highlights and Release Notes:
Qlik Sense June 2020 This release includes new visualizations, like Sparkline Chart, a new Bullet Chart, improvements to the Org chart and a lot more. Check out the recording from Mike Tarallo.
The use of Dynamic Views has been simplified with easier bindings and templates as well as the possibility to load test data in template apps and turn off services in the load script.
Other interesting news for Qlik Sense includes QMC Filters, Advanced LDAP to support Multi Domain setups and support for additional languages for NLP (cloud). Qlik Sense Desktop can now be unlocked against SaaS editions (Business/Enterprise) of Qlik Sense.
Check out the Help site for more information on the features. For resolved issues, please see the Release Notes
Qlik Insight Bot June 2020 Now Supports 3rd party APIs. Changes will need Services engagement.
Qlik NPrinting June 2020 Added support for Custom Themes to be used in reports as well as the possibility to delete reports in NewsStand Please review the Release Notes for more information on the new features and fixes.
Qlik Alerting June 2020 Will enable the use of Qlik Licensing as well as support. The June release also includes support for Internet Explorer, extended security configuration and external database connection settings. Check out the Release Notes for more information and do not lose the opportunity to attend our next STT presentation on Qlik Alerting.
Qlik Replicate Has as new feature Snowflake for Google as a target Endpoint, PostgreSQL as a Source and Target, and the maximum number of tables that can be selected has been increased from 10,000 to 50,000 for Qlik Replicate. Please see the Release Notes.
Qlik Data Catalyst With Data Catalyst there is now support for Keycloak Identity Provider, and mapping for Qlik Data Catalyst and Qlik Enterprise Management Objects. Please see the Release Notes.
Qlik Compose for Data Lakes Improved performance and a newly supported hive distribution which is Databricks on AWS. Another change was signing certificates for Windows binaries that were changed to Qlik certificates.Please see the Release Notes.
Qlik Compose for Data Warehouses Qlik Compose for Data Warehouses release includes new features and improvements. Some of the major features are there is now Data Mart Creation in Snowflake, Newly Supported Data Warehouse for Snowflake on Google Cloud, and Migration of project objects with compare and apply.Please see the Release Notes.
Qlik Enterprise Manager Please see the Release Notes.
The June 2020 releases are now available on the Qlik download site. As with all software, please follow best practices when upgrading by backing up your Qlik Sense or Qlik NPrinting environment and testing the patch in a QA environment first. For Qlik Sense upgrades, please check out the Qlik Sense Upgrade Guide for helpful tips.
Be sure to subscribe to the Qlik Support Blog by clicking the green Subscribe button to stay up-to-date with the latest releases.
Thank you for choosing Qlik!
Kind Regards,
Qlik Global Support
We are now less than 2 weeks away from QlikWorld Online, where all of our Academic Program Datathon winners will be presenting their solutions and you will have the opportunity to vote for your favourite, to crown the overall winner. So that you have the chance to get to know each of the challenge winners ahead of the event, we are highlighting each one in a blog post. Nam Mai is the winner of our first challenge which considers how to maximise the effect of actions taken to fight climate change, whilst also minimising the costs.
Nam Mai is originally from Vietnam where he studied an Economics major before taking his first job as a Business Analyst. Whilst working in this role, Nam Mai first discovered Qlik when he was tasked with finding a solution for automatic reporting. However, he then made the move to France to study a Masters in Statistics and Econometrics at Université Toulouse 1 Capitole, so didn’t get chance to fully utilise Qlik. It wasn’t until this final year of his masters during a Data Visualisation module that he decided to revisit Qlik. He used Qlik Sense for his project where he created visualisations about the various houses registered with Airbnb. Nam Mai commented that “the data modelling aspect is very easy to manage and as the scripting language is based on SQL which I am familiar with, it’s very easy to use. And the diverse choice of visualisations is very useful.”
It was then during an apprenticeship with a digital consulting company that his manager Matthieu Burel (a Qlik Luminary) made Nam Mai aware of the Qlik Academic Program Datathon. Matthieu commented that “this Qlik C40 Datathon is a great opportunity for trainees to confront a real analytics project. Keep in mind that these are really massive data sets to discover and explore with the aim of meeting real social, economic and ecological challenges. It’s a unique opportunity, as a young graduate student, to fully understand the issues from start to finish, from the data preparation to the dataviz design and related storytelling. Finally, this challenge is more than a competition, it requires imagination, creativity and a good dose of innovation! Everything you expect from a future data analyst.”
Nam Mai was instantly excited by the opportunity and was eagerly awaiting the official launch date so that he could register and get to work. He chose to tackle the challenge about maximising the effects of climate action and minimising the costs, as he felt that this is a highly relevant topic for decision makers across all organisations. He was very keen to improve the existing Action Analysis Database available from C40 Cities, to make it more comprehensive and to enable people to make even more informed decisions.
One of the most testing aspects of this challenge was that it involved a lot of text analysis and data cleansing. As Nam Mai was already familiar with Qlik Sense from his data visualisation module at University, he was keen to push himself and to gain more advanced skills. He used various resources to upskill throughout the Datathon, including courses on learning.qlik.com, Qlik Branch and a Facebook community of Qlik users in Vietnam who share a lot of knowledge and tips relating to Qlik. Nam Mai is also very thankful for the invaluable feedback that he received from his Managers during the Datathon.
Another big challenge for Nam Mai of taking part in the Datathon was balancing his time between his apprenticeship, University studies and developing his solution for the challenge. But he is certain that the time that he dedicated to the competition has been well worth it. In fact, he has already promoted the Datathon within his Qlik user Facebook community and plans to encourage his contacts to participate in upcoming datathons.
Nam Mai’s career ambition is to become a BI Professional, so being selected as a winner is a great asset for his CV. Despite being disappointed that he will not have the opportunity to present his solution at the QlikWorld in-person event, it’s clear that QlikWorld Online will still be a great opportunity for him to network and to present his application to an even wider audience. We are excited to see what the future will hold for him! Register today to get your front row seat and to vote for your favourite Datathon solution.
Hello Qlik Users,
It’s Qlik Sense Patch Wednesday!
We have three new Qlik Sense patches available on the Qlik download site:
Qlik Sense Patch | |
September 2019 Patch 11 | |
February 2020 Patch 5 | |
April 2020 Patch 3 |
As with all software, please follow best practices when upgrading by backing up your Qlik Sense environment and testing the patch in a QA environment first. For more guidance on upgrade, see the Qlik Sense Upgrade guide. This guide was put together by the Qlik Digital Support team and offers step-by-step instructions, pictures and troubleshooting tips.
Be sure to subscribe to the Qlik Support Updates Blog by clicking the green Subscribe button to stay up-to-date with the latest releases. Please give this post a like if you found it helpful! Also, please let us know if you have any questions or leave your feedback in the comments.
Thank you for choosing Qlik!
Kind Regards,
Qlik Global Support
Hi everyone,
Want to stay a step ahead of important Qlik support issues? Then sign up for our monthly webinar series where you can get first-hand insights from our #QlikSupport experts.
The Support Techspert Thursday session from June looked at Troubleshooting Qlik Alerting Setup.
But wait, what is it exactly?
Support Techspert Thursdays is a free webinar to facilitate knowledge sharing held on a monthly basis, on the third Thursday of each month.
Hear directly from Qlik Techsperts on topics that are relevant to Customers and Partners today.
In this session we will cover:
• What can Alerting Do?
• Architecture
• Getting started
• Tips and Tricks
Click on this link to see the presentation.
The Aggr() functions is one of the most advanced functions in the QIX engine, and it is not always easy to use. It does not get easier when you put set analysis expressions in it.
In one of my previous posts (Pitfalls of the Aggr function) I recommended having the set analysis expression in both the inner and the outer aggregation function when using set analysis in the Aggr() function. This is a good rule of thumb, because in most cases doing so will generate the result that you want.
But this is not always correct.
In more complex calculations you often need to use the condition in one place only – sometimes in the inner aggregation, sometimes in the outer. It depends on how the condition is formulated. Then it is important to understand the difference between the two positions.
The evaluation of the Aggr() function is a two-step process: In the first step, an intermediary virtual table is created using the inner aggregation and the dimension of the Aggr(). In the second step, this virtual table is aggregated using the outer aggregation.
For example, say that you want to find the largest order value per year. Then you would need to first calculate the sales value per order, and in a second step find the largest of these values. Hence
The first step aggregates the source data (with multiple records per Order ID) into a virtual table with one record per Order ID, and the second step finds the largest values in the virtual table.
However, there is not yet any set analysis in the expression. So, let us use the following requirement instead:
The two conditions correspond to the following set analysis expression:
But where should this expression be written? In the outer or in the inner aggregation?
To answer this question, we must ask ourselves in which step the conditions should be used. Then it becomes obvious that the condition in product group must be used in step one – in the inner aggregation. If it is used in the outer aggregation only, the order values will be incorrect – they will be calculated from all products.
The condition in year, however, can be put in either place. Hence, the following expression will work fine:
From the above example one might draw the conclusion that you always should put the condition in the inner aggregation. But this is not the case. Sometimes you have a condition that cannot be put in the inner aggregation. The following requirement can serve as example:
The solution is the following table
The condition in product group should be evaluated in step two, so the expressions used for Product and Rank are:
Here it is not possible to have the condition on product group in the inner aggregation, since this would interfere with the calculation of the rank. You must have it in the outer aggregation.
Bottom lines are:
Further reading related to this topic:
Today’s post is all about Pauline Guillet from Université de Technologie de Compiègne in France. Pauline is the well deserving winner of the second challenge in the Qlik Academic Program Datathon, which focused on tackling air pollution and climate change together. Pauline opted to take part in this challenge in particular, as she saw this as a great opportunity to learn more about air pollution as well as climate change more broadly, and to challenge her skills. Pauline commented that “we hear a lot about it (climate change) on TV and all of the associated problems, but as citizens we don’t know about these issues in depth.”
Pauline is currently in her final year of a Master’s in Computer Science specialising in Data and Business Intelligence, but she didn’t always know what she wanted to study. She tried statistics after her French baccalaureate because she liked figures at high school, and from there she found her passion. So, she has continued that path ever since and is planning to pursue a career in data science.
Pauline first discovered Qlik whilst working on an internship in February of this year. After a week of introductory training, her manager suggested that she take part in the Datathon as a way to improve her skills and experience in Qlik Sense. From there, Pauline used the many online resources available to upskill in the software, including the self-paced learning and interactive videos available on learning.qlik.com. Pauline said, “the videos are really clear and not too fast, so can be easily understood. The platform is a great resource.”
Despite her enthusiasm for taking part in the Datathon, Pauline inevitably had hurdles to overcome along the way. Improving her application from the first draft to the final version was a challenging process, but she completed this successfully with the help of guidance from Qlik Luminary Matthieu Burel and by taking inspiration from Qlik demo applications online. Another big challenge she faced was finding the story in her data, something that many analysts will be familiar with. Pauline described it as “searching for the holy grail!” and was very satisfied, and relieved to finally find it.
When asked if she would recommend taking part in future datathons, Pauline remarked that “practice is the best way to learn, so the Datathon is a great way to facilitate this. Even if you don’t win, because I really didn’t expect to win, there are only benefits of taking part because you are learning, and this is the most important thing.” As well as gaining new skills Pauline was also keen to add that the knowledge that she has gained around climate change and air pollution has really impacted the way that she lives her day to day life and the decisions that she makes. “When you have the knowledge, you can act in the best way for the planet.”
Pauline is excited to present alongside the other Datathon winners at QlikWorld Online 2020. Register now to discover the story that she found in her data, to drive positive change for our planet, and don’t forget to vote for your favourite solution and help Qlik award the overall winner of the Datathon!