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Product Innovation
By reading the Product Innovation blog, you will learn about what's new across all of the products in our growing Qlik product portfolio.
Support Updates
The Support Updates blog delivers important and useful Qlik Support information about end-of-product support, new service releases, and general support topics.
Qlik Academic Program
This blog was created for professors and students using Qlik within academia.
Community News
Hear it from your Community Managers! The Community News blog provides updates about the Qlik Community Platform and other news and important announcements.
Qlik Digest
The Qlik Digest is your essential monthly low-down of the need-to-know product updates, events, and resources from Qlik.
Qlik Learning
The Qlik Learning blog offers information about the latest updates to our courses and programs, as well as insights from the Qlik Learning team.
Recent Blog Posts
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From Raw Data to AI-Ready: Accelerating GenAI and Agentic Initiatives with Qlik ...
Most enterprise AI projects don’t fail because the model is wrong. They fail because the data isn’t ready. Data engineering leaders are now being asked to support a new wave of generative and agentic workloads that demand fresher data, broader source coverage, tighter governance, and richer context than traditional BI ever required — and to deliver it without growing the team. Qlik Talend Cloud Data Integration was built to close that gap. It pro... Show MoreMost enterprise AI projects don’t fail because the model is wrong. They fail because the data isn’t ready. Data engineering leaders are now being asked to support a new wave of generative and agentic workloads that demand fresher data, broader source coverage, tighter governance, and richer context than traditional BI ever required — and to deliver it without growing the team.
Qlik Talend Cloud Data Integration was built to close that gap. It provides a single, governed pipeline from operational sources to an open lakehouse — and on to the vector indexes, feature stores, and APIs that your AI systems actually consume. Combined with Qlik Open Lakehouse on Apache Iceberg, it turns your AI inputs into reusable AI data products: named, versioned, governed assets that any RAG application or agent can consume off the shelf.
This post walks through the reference architecture, the pipeline that produces those data products, and a worked example that takes raw CRM and product data all the way to a working RAG copilot and an agentic workflow — both running off the same Iceberg foundation.
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Unlocking Qlik Open Lakehouse Access from Talend Studio
Talend Studio now connects natively to Qlik Open Lakehouse — query Iceberg-managed data directly from your existing Standard and Big Data jobs, with no manual JDBC configuration required. Learn how this integration works and what it means for your data workflows. -
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SAP S/4HANA 移行の「壁」を突破する！テストデータ管理を劇的に変える！
2027年の「SAP 2027年問題」のタイムリミットが迫る中、多くの企業が S/4HANA への移行プロジェクトを進めています。しかし、移行の現場で深刻なボトルネックとなっているのが「テスト環境の構築」と「データの肥大化」です。 -
The New Write Table
The write table was introduced to Qlik Cloud Analytics last month so in this blog post, I will review how it works and how it can be added to an app. The write table looks like the straight table but editable columns can be added to it to update or add data. The updated/added data is visible by other users of the app provided they have the correct permissions. Read more on write table permissions here. Something else to note, if using a touch scr... Show MoreThe write table was introduced to Qlik Cloud Analytics last month so in this blog post, I will review how it works and how it can be added to an app. The write table looks like the straight table but editable columns can be added to it to update or add data. The updated/added data is visible by other users of the app provided they have the correct permissions. Read more on write table permissions here. Something else to note, if using a touch screen device, is you will have to disable touch screen mode for the write table to work. Looking at the write table for the first time, I found it intuitive and easy to use. Let’s create a write table with some editable columns to see how easy it is.
The write table object can be added to a sheet like any other visualization. Once it is added, columns can be added the same way dimensions and measures are added to a straight table. Below is a small write table with course information including the course ID, course name, instructor and location.
To add an editable column from the properties panel, click on the plus sign (+) and select Editable column.
The new editable column will be added. In the properties for the column, the title for the column can be modified and from the show content drop down, manual user input or single selection can be selected. Manual user input will create a free form column that the user can type into. The single selection option will allow me to create a drop-down list of options that the user can choose from.
I will change the title to Course Level and for show content I will select single selection and add three list items by typing the list item and then clicking on the plus sign to add it to the list. The list items will be displayed in the drop-down in the order they are added but can be rearranged by hovering over the list-item and dragging it to the desired position. List-items can also be deleted by hovering over it and clicking the delete icon that appears to the left.
When you come out of edit mode, the message below will appear for the editable column prompting you to define a set of primary keys.
Once you click Define, you will see the pop-up below where you can select the column(s) that will be used for the unique primary key. This is necessary to save and map the data entered in the editable column to the data model. I will select the CourseID column as the primary key.
Once this is done, I will see the Course Level column with the drop-down of list-items I added.
Let’s add one more editable column that takes manual user unput and name it Notes.
As I add data or update the editable columns, the cells will be flagged orange to indicate that my edits have not been saved. Once I save the table, they will be flagged green and any new values entered are visible to other users. A cell will be blue if another user is currently making changes to the row, thus locking it. Changes are saved for 90 days in a change store (temporary storage location) provided by Qlik. After 90 days, the data will be deleted. It is also important to note that if an editable column is deleted, the data will be lost. This is also the case if the primary key used for the editable column is removed.
It is possible to retrieve the changes from a change store via the change-stores API or an automation. Using the REST connection and the change-store API, the changes made in a write table can be retrieved and stored in a QVD (if needed for more than 90 days) or added to the data model for use in other analytics. Qlik Automate can also be used to retrieve data from the change-store using the List Current Changes From Change Store block or the List Change Store History block. From there the data can be stored permanently in an external system for later use or used in the automation for another process. Qlik Help offers steps for retrieving data from a change-store.
The write table can make it easy for users to add updates, feedback and important information that may not be available in the data model. Not only can this be done quickly, but it can be immediately visible to other colleagues. Learn more about the write table in the Product Innovation blog along with links to videos and write table FAQs.
Thanks,
Jennell
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Upcoming Maintenance for Talend Cloud and Talend Management Console: March, Apri...
Update March 4th, 2026: added link to How to get Talend Management Console task schedules and pause and resume during a maintenance window using the API articleUpdated April 24th, 2026: added impact on APIs (all down) and additional clarification on why tasks must be stopped and the impact on remote enginesUpdated May 7th, 2026: added additional information on how to address Remote Engine impact Talend Cloud and Talend Management Console will und... Show MoreUpdate March 4th, 2026: added link to How to get Talend Management Console task schedules and pause and resume during a maintenance window using the API article
Updated April 24th, 2026: added impact on APIs (all down) and additional clarification on why tasks must be stopped and the impact on remote engines
Updated May 7th, 2026: added additional information on how to address Remote Engine impactTalend Cloud and Talend Management Console will undergo scheduled maintenance in March, April, and May. This infrastructure modernization is a key step in unifying the Talend ecosystem with Qlik.
The alignment paves the way for a more seamless experience across both platforms. Over the coming months, you will gain access to integrated features that bridge data integration and analytics, enabling unified governance and a streamlined management experience across your entire data lifecycle.
The maintenance windows will occur per region, during off-peak hours, and are expected to have a maximum of 30 minutes of effective downtime.
What is the expected impact?
A full outage of Talend Cloud and Talend Management Console for a duration of up to 30 minutes within a preplanned 4-hour window.
The following applications will not be accessible:
- Talend Management Console (TMC)
- Talend Data Stewardship (TDS)
- Talend Data Preparation (TDP)
- Talend Data Inventory (TDC)
- Talend Pipeline Designer (TPD)
- Talend API Designer and Tester
- Talend Studio
- Talend Cloud Engines
All APIs for Talend Cloud will not be available during the outage. APIs impacted:
In detail:
- Cloud engines will not be available, and executions running on Cloud Engines will be terminated.
- Talend Studio users may be disconnected from their session, and it will not be possible to open a new Talend Studio session except in local mode.
- Executions that are already in progress during the outage will terminate correctly except on cloud engines, but all tasks or plans scheduled to start during those periods will be skipped.
- Skipped executions will not be tagged as failed, since they were never started. For this reason, check the execution status of your tasks and plans to ensure that all important ones are not skipped, or start them manually if necessary. See What do I need to do to prepare? further down in this blog post.
- Static IP addresses for Cloud Engines corresponding to Disaster Recovery regions will change during maintenance. See What follow-up actions are required? further down in this blog post.
What do I need to do to prepare?
- It is recommended to pause existing task runs during the maintenance window. Talend Remote Engines will continue processing tasks during the outage if they started before the maintenance window, but as they may have inconsistent statuses, we recommend pausing all tasks beforehand.
This concerns all jobs and plans scheduled to start or run during the maintenance window.
See Checking scheduled task runs against your maintenance timetable on how to identify these plans and jobs.Looking for information on how to identify, pause, and resume your tasks? See How to get Talend Management Console task schedules and pause and resume during a maintenance window using the API.
- If you are running Remote Engine Gen2, upgrade to the latest 2026-04. This is to prevent RE Gen2 from becoming unavailable after the maintenance. To do so:
- Upgrade your Remote Engine Gen2 to the latest 2026-04 release: Updating the Remote Engine Gen2 when installed using the execution script)
- Then re-establish the pairing: Re-establish the pairing of Remote Engine Gen2
What follow-up actions are required?
- After the maintenance window, check and monitor the execution status of tasks and plans, as well as the status of your Remote Engines.
In some instances, Remote Engines might require a restart if marked as unavailable in the Talend Management Console or if tasks cannot be executed as expected.
If restarting the Remote Engine does not resolve the complication, follow the pairing instructions in Pairing Remote Engines using a dedicated web service to reset the key and re-pair the Remote Engine.
If your Remote Engine Gen2 is unavailable or cannot execute tasks, then:
- Upgrade your Remote Engine Gen2 to the latest 2026-04 release: Updating the Remote Engine Gen2 when installed using the execution script)
- And re-establish the pairing: Re-establish the pairing of Remote Engine Gen2
- If you use a predefined static IP on Cloud Engine, you will need to allow the new Disaster Recovery Region's IP addresses, which will have changed at this point. While this does not immediately affect production, it will impact any potential Disaster Recovery process.
After the maintenance window, check your static IPs (Disaster Recovery) as documented in Using predefined static IP addresses for execution containers and update your firewalls accordingly.
No change is required for the active region's IP addresses. They will be migrated and will work as of today, ensuring no production interruption.
When will the maintenance take place?
Each region will undergo maintenance for 4 hours during off-peak hours, with a maximum of 30 minutes of effective downtime.
Region Maintenance Start Maintenance End Talend Cloud - AWS - Asia Pacific (Sydney)
au.cloud.talend.com
Wednesday 25 March 2026
22:00 AEDT (Sydney)UTC: 25/03/26 - 11:00
Thursday 26 March 2026
02:00 AEDT (Sydney)UTC: 25/03/26 - 15:00
Talend Cloud - AWS - Asia Pacific (Tokyo)
ap.cloud.talend.com
Monday 20 April 2026
22:00 JST (Tokyo)UTC: 20/04/26 - 13:00
Tuesday 21 April 2026
02:00 JST (Tokyo)UTC: 20/04/26 - 17:00
Talend Cloud - AWS - US East (N. Virginia)
us.cloud.talend.com
Monday 27 April 2026
02:00 EDTUTC: 27/04/26 - 6:00
Monday 27 April 2026
06:00 EDTUTC: 27/04/26 - 10:00
Talend Cloud - AWS - Europe (Frankfurt)
eu.cloud.talend.com
Tuesday 26 May 2026
21:00 CESTUTC: 26/05/26 - 19:00
Wednesday 27 May 2026
01:00 CESTUTC: 26/05/26 - 23:00
To identify which region your tenant is affected by, cross-reference Accessing Talend Cloud applications.
To track further updates during the scheduled Qlik Cloud Maintenance, please visit our Qlik Cloud Status page. This blog post will be updated with additional information where necessary.
Thank you for choosing Qlik,
Qlik Support -
Do More with Qlik
Today I want to introduce you to a gem that you may be missing out on. It is the Do More with Qlik community forum lead by @Michael_Tarallo . This forum is made up of concise videos that cover everything from Qlik capabilities to innovative ways to solve business challenges. It is for users of all levels, beginners to seasoned Qlik users, with a wide range of topics. Check out this introductory video to learn more and bookmark the forum. You do... Show MoreToday I want to introduce you to a gem that you may be missing out on. It is the Do More with Qlik community forum lead by @Michael_Tarallo . This forum is made up of concise videos that cover everything from Qlik capabilities to innovative ways to solve business challenges. It is for users of all levels, beginners to seasoned Qlik users, with a wide range of topics. Check out this introductory video to learn more and bookmark the forum. You do not want to miss out on this!
Thanks,
Jennell
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Beyond Dashboards: Preparing Students for the Future of AI-Powered Analytics
For many years, data analytics education focused primarily on building dashboards and visualizing historical data. While these skills remain important, the analytics landscape is rapidly evolving. Today, organizations are looking for graduates who can do far more than create charts and reports. They need students who can work with AI-powered analytics, understand predictive thinking, and interact with data in more intelligent and conversational w... Show MoreFor many years, data analytics education focused primarily on building dashboards and visualizing historical data. While these skills remain important, the analytics landscape is rapidly evolving. Today, organizations are looking for graduates who can do far more than create charts and reports. They need students who can work with AI-powered analytics, understand predictive thinking, and interact with data in more intelligent and conversational ways.
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Upcoming removal of GET method for /api/v1/apps in Qlik Cloud Analytics, May 202...
Update, 6th of May 2026: This is now deployed in all regions. Previously, the /api/v1/apps endpoint could be used to list all apps on a tenant. This method has always been unsupported and undocumented, and will be removed in the first week of May 2026. How will this affect me? If you are currently using /api/v1/apps, switch to GET with /api/v1/items instead. This can be further filtered by choosing a resource type (such as /items?noActions=tr... Show MoreUpdate, 6th of May 2026: This is now deployed in all regions.
Previously, the /api/v1/apps endpoint could be used to list all apps on a tenant. This method has always been unsupported and undocumented, and will be removed in the first week of May 2026.
How will this affect me?
If you are currently using /api/v1/apps, switch to GET with /api/v1/items instead.
This can be further filtered by choosing a resource type (such as /items?noActions=true&resourceType=app, /items?noActions=true&resourceType=script, or similar).
What about similar requests?
- GET with /api/v1/apps/APPID for a specific app will keep on working
- POST with /api/v1/apps will also keep on working
For more information, see:
If you have any questions, we're happy to assist. Reply to this blog post or take your queries to our Support Chat.
Thank you for choosing Qlik,
Qlik Support -
Finance Report with Waterfall Chart
Several years ago, I wrote a blog post on how to create a profit and loss statement in QlikView. @Patric_Nordstrom has built upon this method and built a financial statement in Qlik Analytics with a straight table and waterfall chart using inline SVG. In this blog post, I will review how he did it. Here is an example of the financial statement structure. There are plain rows, such as gross sales and sales return where the a... Show MoreSeveral years ago, I wrote a blog post on how to create a profit and loss statement in QlikView. @Patric_Nordstrom has built upon this method and built a financial statement in Qlik Analytics with a straight table and waterfall chart using inline SVG. In this blog post, I will review how he did it.
Here is an example of the financial statement structure.
There are plain rows, such as gross sales and sales return where the amount is the sum of the transactions made against the accounts. There are subtotals such as net sales and gross margin which are a sum of the previous plain rows. And there are also partial sums such as total cost of sales that is a sum of a subset of the previous plain rows, but not all the previous plain rows.
Patric identified two functions, RangeSum() and Above() that are suitable for calculating the subtotal and partial sums in a table. The RangeSum function sums a range of values, and the Above function evaluates an expression at a row above the current row within a column segment in a table. The above function can be used with 2 optional parameters – offset and count to further identify the rows to be used in the expression.
The layout table below is used as a template for the financial statement.
- The RowStyle column is used for styling the rows making text bold or underlining it. Currently, we cannot use tab or blank tags but hopefully in the future this will become available in the straight table.
- The RowTitle is the account category that is to be used in the financial statement.
- RowType is used to as input to calculate the offset and count for the above function.
- AC is the actual amount.
The AC column is included here in the layout file for demo purposes but could be calculated from the accounts and transactions in the data model as well.
In the script, the layout table was loaded, and additional fields were created to support the waterfall chart, specifically offset and count fields to be used with the above function.
Here is a view of the layout table with the new fields that were created in the script.
After the layout table is loaded and the new fields are created, some master measures can be created to be used in the inline SVG expression. Here are the 3 master measures Patric created:
mBar is the bar length with an offset that is always 0.
mStart is the starting position of the bar in the waterfall chart and for subtotals, this is always 0.
mMax is the max bar length which is used to scale the bars in the waterfall chart.Now the straight table can be created. The RowNr field is added for sorting purposes. The RowTitle field and the AC fields are added to show the account groupings in the financial statement along with their value. The below inline SVG expression for the waterfall chart is the last column added to the straight table. It is made up of 3 parts:
- A plain line with an offset
- A thin gray line where x=0
- A label
- The if statement on line 1 will determine if a bar is displayed. Bars will only be visible if the RowStyle is not blank.
- Line 2 has the viewBox settings and sets the 0 for the x-axis.
- On line 3 is the light gray line where x=0 and it is displayed on all non-blank rows of the financial statement.
- Lines 4 and 5 in the yellow box is the plain line with the offset, scaled using the mMax measure to control the length of the line.
- Line 6 handles the bar color, light green for positive values and red for negative values.
- On line 7, the if statement is used to set the stroke width of the bar. A thin line is used if the RowType is retrosum and a wider line is used for all other bars.
- In the red box, on lines 10 through 13, the label text is set and placed either to the left or right of the bar depending on the value. Positive values are placed to the right of the bar and negative values are placed to the left of the bar.
The result of the financial statement looks like this:
To add the text styling (bold and underline) from the layout table, the RowStyle field was added to the text style expression in the RowTitle and AC columns.
Indentation is added by using the repeat function in the RowTitle column. It will repeat a non-breaking space 6 times if there is a tab tag in the RowStyle field. Otherwise, no indentation is done.
If the RowStyle is not blank, a bar is displayed for the waterfall chart and the sum value for the actual amount (or mBar) in this case is displayed.
The chart column representation is set to Image in the properties of the straight table.
While this method looks complex, it is a simple and clean solution for adding a waterfall chart to a financial statement using straight table features and inline SVG. Using the layout table and inline SVG provides room for customization so that the financial report meets the needs and requirements of the user or customer.
Thanks,
Jennell
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Color Palette
Color Pallete Nitin This Dashboard defines a set of predefined colors used to help maintain consistency and clarity across the dashboard, it help to find easily color code and how it will looks Discoveries These shift focus on reducing time to find out best colors and color coding that would improve speed to choose colors, and color combination can improves user sections Impact The Primary impact of this well designed palette... Show MoreColor PalleteNitin
This Dashboard defines a set of predefined colors used to help maintain consistency and clarity across the dashboard, it help to find easily color code and how it will looks
Discoveries
These shift focus on reducing time to find out best colors and color coding that would improve speed to choose colors, and color combination can improves user sections
Impact
The Primary impact of this well designed palette is reducing the mental effort of choosing colors. it helps user to refer multiple colors side by side and check which color and suitable for each dimension. and
Audience
All dashboard developers
Data and advanced analytics
The Color are always act as a bridge between complex raw data executive decision making. its help to choose right matching colors with color code and help to reduce check each color one by one and see how it looks
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Knowledge Nuggets 2026(Q1)
Knowledge Nuggets - 2026(Q1) Insight Consulting A collection of Qlik and Data & AI Literacy related videos and articles Discoveries Contributors and Keywords Impact Learning resource Audience All Qlik stakeholders Data and advanced analytics Learning resource -
QlikView server communication interruptions following Microsoft Windows Domain C...
Edited May 4th, 2026: Added mitigation article, published on the 4th of May. Beginning on April 14, 2026, multiple QlikView customers experienced outages and intermittent disruptions within their QlikView environments. These incidents coincided with the deployment of Microsoft’s April 2026 security patches to Domain Controllers, which affected QlikView Server Service (QVS) communications over port 4747. The Microsoft patches introduced changes ta... Show MoreEdited May 4th, 2026: Added mitigation article, published on the 4th of May.
Beginning on April 14, 2026, multiple QlikView customers experienced outages and intermittent disruptions within their QlikView environments. These incidents coincided with the deployment of Microsoft’s April 2026 security patches to Domain Controllers, which affected QlikView Server Service (QVS) communications over port 4747.
The Microsoft patches introduced changes targeting Kerberos authentication and RC4 encryption. See Addendum for a list of patches. As a result, QlikView environments where RC4 remained enabled (such as at the domain account or Windows server level) became unstable or non-functional.
The impact on QlikView may include, but is not limited to:
- Failed QlikView Distribution Server distribution tasks with an error code indicating an Authentication Failure.
- "No Server" message on the QlikView AccessPoint with an error message in the Web server log indicating that the Web server cannot connect to the QlikView Server.
- Failed Qlik NPrinting distributions to QlikView using a QVP Connection.
- Problems accessing the QlikView Server settings from the QlikView Management Console, or failures for the QlikView Server to come online after a restart.
What can be done to mitigate this issue?
We've published an article to help address the issue. See QlikView server communication interruptions following Microsoft Windows RC4 cipher suite deprecation.
Information in the article is based on Microsoft's remediation steps and has been adjusted and expanded to include QlikView-specific instructions. For the original, see Detect and remediate RC4 usage in Kerberos | learn.microfot.com.
What action is Qlik taking?
RC4 support was deprecated starting with the May 2024 release of QlikView. The root cause in these cases stems from legacy configurations where RC4 remained enabled in the environment, rather than a defect in QlikView itself. No code changes are planned at this time, though improvements to diagnostic logging are under consideration.
Addendum
Microsoft Patches:
- Windows Server 2022 (DC): KB5082142
- Windows Server 2019 (DC): KB5082123
- Windows Server 2016 (DC): KB508208
If you have any questions, we're happy to assist. Reply to this blog post or take your queries to our Support Chat.
Thank you for choosing Qlik,
Qlik Support -
Introducing the QlikView to Qlik Sense Cloud Converter Tool (QV2QS)
Are you still looking to convert your QlikView environment to Qlik Cloud, but find the concept of migrating each of your apps daunting? Then Qlik has the answer for you. QlikView to Qlik Sense Converter Tool – SaaS in 60 We've introduced the QlikView to Qlik Sense Converter Tool (QV2QS), which delivers ready-to-use Qlik Sense apps complete with sheets, layout, expressions, and data. Better yet, it deploys them directly to your Qlik Cloud tenant,... Show MoreAre you still looking to convert your QlikView environment to Qlik Cloud, but find the concept of migrating each of your apps daunting? Then Qlik has the answer for you.
QlikView to Qlik Sense Converter Tool – SaaS in 60
We've introduced the QlikView to Qlik Sense Converter Tool (QV2QS), which delivers ready-to-use Qlik Sense apps complete with sheets, layout, expressions, and data. Better yet, it deploys them directly to your Qlik Cloud tenant, all of which reduces your conversion times from hours to minutes.
What's included?
Developed and supported by Qlik, QV2Q can:
- Convert .qvw files to Qlik Sense apps, including complete sheets, layout, styling, expressions, and 25+ object types
- Recreate sheet layouts 1:1, preserving the position and formatting of your QlikView visualizations
- Bridge the feature parity gap and convert alternate states, conditional show/hide, cycle or drill-down groups, and more!
- Deploy directly to Qlik Cloud with data reload
- Produce an Excel report and an HTML executive summary dashboard
- Support single-app and parallel batch conversion
Why use QV2QS?
While other converters produce master items from a subset of charts and tables (no sheets, no layout, no text objects, buttons, containers, or backgrounds), QV2QS delivers complete, ready-to-use apps.
Not only that, but migrating to Qlik Cloud using QV2Q2 will also enable you to:
- Preserve dashboards and expressions while unlocking Qlik Answers, Qlik Predict, Qlik MCP, Qlik Automate, and the Qlik Reporting Service
- Eliminate servers, patching, and legacy licensing costs
- Compress months of work into days with familiar dashboards available on day one
- Redesign at your own pace with no big bang required
Are you ready to get started?
QV2QS is built for Qlik consultants, QlikView developers, Qlik Sense developers, BI teams, and IT administrators migrating from QlikView to Qlik Sense. QV2QS runs as a standalone Windows executable with two interfaces: a guided web-based wizard and a command-line interface.
Here's what you will need:
- Review the full documentation at QlikView to Qlik Sense Converter Tool | Help.qlik.com
- Download the QlikView to Qlik Sense Converter from the Qlik Download Page
Tip: Select Search All, then search for QlikView to Qlik Sense in the Product field. - Check out our SaaS in 60 - QlikView to Qlik Sense Converter tool video
Thank you for choosing Qlik,
Qlik Support -
Techspert Talks - Migrating QlikView to Qlik Cloud
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 Qlik experts. The Techspert Talks session from April looked at Migrating QlikView to Qlik Cloud. But wait, what is it exactly? Techspert Talks is a free webinar held on a monthly basis, where you can hear directly from Qlik Techsperts on topics that are relevant to Customers and Partner... Show MoreHi 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 Qlik experts.The Techspert Talks session from April looked at Migrating QlikView to Qlik Cloud.
But wait, what is it exactly?
Techspert Talks is a free webinar held on a monthly basis, where you can hear directly from Qlik Techsperts on topics that are relevant to Customers and Partners today.
In this session we will cover:
- Converting QlikView documents to Sense Apps
- Qlik Cloud Advantages
- Migration Tools
Click here to see the presentation
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Financial Analysis
As a follow-up to my previous blog post titled Finance Report with Waterfall Chart, I wanted to share an awesome demo that showcases financial reporting visualizations including a profit & loss statement with a waterfall chart. Qlik's Dennis Jaskowiak and Ekaterina Kovalenko, and partner Dawid Marciniak from HighCoordination, created the Financial Analysis demo based off of Jedox data, incorporating many enhancements to the straight table and piv... Show MoreAs a follow-up to my previous blog post titled Finance Report with Waterfall Chart, I wanted to share an awesome demo that showcases financial reporting visualizations including a profit & loss statement with a waterfall chart. Qlik's Dennis Jaskowiak and Ekaterina Kovalenko, and partner Dawid Marciniak from HighCoordination, created the Financial Analysis demo based off of Jedox data, incorporating many enhancements to the straight table and pivot table. In addition to the waterfall chart, they use inline SVG to create lollipop charts and bar charts in financial statements.
Here is a look at some of the sheets:
The Dashboard provides a high-level overview of profit and loss, cash flow and liquidity. On this sheet, view the use of inline SVG bar charts and lollipop charts.
The P&L sheet provides a more detailed look at profit and loss.
The Cost Center sheet uses the pivot table to show sales costs.
Find a detailed look of cash flow on the Cash Flow sheet.
This is just some of the sheets you will find in the Financial Analysis demo. If you are looking for appealing ways to visual your financial data while keeping it concise and clean, download the Financial Analysis demo here.
Thanks,
Jennell
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Building a World Cup Bracket App powered by Qlik
With less than 50 days to go before the 2026 World Cup kicks off across the US, Canada, and Mexico, I wanted to share a project I've been working on that brings together a few pieces of the Qlik platform I think work really well together: Choose Your Champion 2026. It's a web app where anyone can fill out their World Cup bracket, get AI-powered predictions for every possible matchup in the tournament powered by Qlik Predict, explore historical Wo... Show MoreWith less than 50 days to go before the 2026 World Cup kicks off across the US, Canada, and Mexico, I wanted to share a project I've been working on that brings together a few pieces of the Qlik platform I think work really well together: Choose Your Champion 2026.
It's a web app where anyone can fill out their World Cup bracket, get AI-powered predictions for every possible matchup in the tournament powered by Qlik Predict, explore historical World Cup data, and compete on a leaderboard as the competition unfolds.
You can try it here: https://webapps.qlik.com/choose-your-champion-2026/index.html#/
The app is powered by Qlik, with Qlik Cloud Analytics for the data model and Historical Analysis, Qlik Predict for the matchup predictions, and various Qlik APIs to wire everything into a React front-end.
In this post, I'll walk through how the predictions work under the hood, because that was the most interesting piece to build.
What's in the app:
Choose Your Champion is broken into 4 parts:
- Build a bracket: Pick your group stage winners, advance teams through the knockout rounds, and lock in your champion.
- Check the predictions: For every possible matchup in the tournament, the app surfaces a Qlik Predict generated win probability for each team plus a draw probability. When you're unsure about a matchup, you can pull up the prediction and use it to decide which team advances.
- Explore historical World Cup data: The app includes various visualizations to help you uncover insights from past tournaments: goals, top scorers, host nation performance, biggest upsets. All powered by the associative engine.
- Leaderboard: As real matches get played in June and July, submitted brackets are scored automatically and players are ranked in the leaderboard table.
Under the hood: how the predictions work
This was the fun part. The goal was simple, given two national teams, predict the outcome of a hypothetical match (team A wins / draw / team B wins), but the work that makes the predictions actually useful is mostly in the data, not the model (thanks to no-code ML with Qlik Predict).
1. The training dataset
I started with every international football match result from 1872 to March 2026. There's a well-maintained open dataset on GitHub (credit: martj42/international_results) that gets updated after every international window, about 49,000 matches in total.
From that raw history, I built a training dataset focused on the modern era (2010 onwards) and only competitive matches (qualifiers, continental tournaments, World Cup finals). Friendlies got filtered out because they're noisy since teams often don't play their A squads, and the stakes don't match what happens in a real tournament.
That left me with around 9,400 training rows, each representing a real historical match with a known result, enriched with 27 features describing both teams' state going into that match:
- Elo ratings for both teams
- FIFA rankings and points snapshot to the match date
- Rolling 10-match form per team: win rate, goals for, goals against, goal difference
- Head-to-head history in the last 10 meetings
- Context flags: neutral venue, tournament tier, cross-confederation
- World Cup pedigree: a score rewarding teams for deep runs in past tournaments, with more recent success weighted heavier
2. ML Experiment
Once the training CSV was in shape, I uploaded it to Qlik Predict, pointed at the result column as the target, and let it do its thing. This is where Qlik Predict really shines, zero code needed. No Python notebooks, no sklearn, no hyperparameter grids to tune. You just upload your data, pick a target, and it does the heavy lifting with full explainability on the outcomes and what drives the predictions.
Qlik Predict runs multiple algorithms in parallel: LightGBM, CatBoost, XGBoost, Random Forest, and a few others, tunes their hyperparameters, and picks the best performer by F1.
On my first run, I left all the columns in the dataset checked, including the team name columns (team_a, team_b). When I looked at the SHAP importance chart afterward, team_b and team_a were ranking as the #2 and #3 most influential features, meaning the model was essentially learning "team X usually wins" rather than learning from the engineered features.
I created a new version, went back to the Data tab, unchecked the team name columns and a few date fields (which were also ranking higher than they should), and re-ran the experiment. Qlik Predict automatically dropped several more low-importance features during training, leaving a clean, focused feature set. The F1 did not change a lot (stayed at ~0.50), but the SHAP chart now showed the model leaning on exactly the signals we want:
- elo_diff
- rank_diff
- is_neutral
- h2h_team_a_advantage
etc...
A few other calls that mattered:
- Filtering to competitive matches only. A friendly between a top side's B squad and a mid-tier opponent tells you almost nothing about what happens in a World Cup group stage game.
- Exponential decay on World Cup pedigree. A deep run in 1970 still counts, but less than one in 2022.
- Removing rows with too many missing features. FIFA rankings don't go back to the 90s for every team, so some rows had to get dropped.
3. The apply dataset
Training gives you a model and to use it, you need an apply dataset with new rows you want predictions for.
For Choose Your Champion, I generated every possible pairing of the 48 qualified teams, which comes out to 1,128 unique matchups. Each row has the same 27 features as the training dataset, but computed as a current snapshot: each team's Elo today, their current FIFA ranking, their most recent 10-match form, and so on.
I fed that into the deployed model and got back a probability distribution for every matchup: P(team_a_win), P(draw), P(team_b_win).
The web app
The web app is a React front-end that connects to the Qlik tenant over anonymous access via @qlik/api, so users never see a login screen or have to authenticate against a tenant. The bracket UI pulls predictions from the Qlik Sense data model, so whenever a user opens a matchup, they're looking at data straight from Qlik.
For the historical World Cup section, I used a mix of @qlik/embed components when I needed a quick, ready-to-use chart, and custom nebula.js + picasso.js visualizations when I needed more control over the styling to match the app's look and feel. Both approaches work against the same underlying Qlik Analytics app, so everything stays consistent and governed in one place.
A few takeaways
If you're thinking about building something similar, a few things worth keeping in mind:
Spend the time on feature engineering. The difference between a model that predicts noise and one that predicts football is almost entirely in the features. Qlik Predict handles algorithm selection and tuning well, but it can only work with what you feed it.
The integration is where Qlik Predict pays off. Once a model is deployed, scoring a new dataset and pulling scores back into a Qlik Cloud Analytics app takes one load script. No Python services to maintain, no separate MLOps platform to stand up, no JSON plumbing between systems. That end-to-end data prep, modeling, predictions, and analytics all living in one platform is the thing that made this project come together fast!
The World Cup starts June 11, so there's plenty of time to get your bracket in and earn your spot on the leaderboard before kickoff. If you're curious about how any of this was built, leave a comment or reach out to me directly!
And if you want to learn more about Qlik Predict and start using it, visit: https://www.qlik.com/us/products/qlik-predict
P.S: I have attached both Training and Apply datasets if you'd like to use them in your own Qlik Predict experiment.
Thank you! -
Action required: Update your Qlik Automate Salesforce connector authentication o...
Salesforce is rolling out mandatory security updates to how connected apps handle OAuth authentication. What does this mean for me? To keep your Qlik Automate Salesforce connector working after Tuesday, 5th May 2026, you'll need to take a quick, one-time action: update a setting in your connection and re-authenticate to Salesforce. This cannot be done automatically, nor can it be done before the release. A manual step is required on or after th... Show MoreSalesforce is rolling out mandatory security updates to how connected apps handle OAuth authentication.
What does this mean for me?
To keep your Qlik Automate Salesforce connector working after Tuesday, 5th May 2026, you'll need to take a quick, one-time action: update a setting in your connection and re-authenticate to Salesforce.
This cannot be done automatically, nor can it be done before the release. A manual step is required on or after the 5th of May.
Why is this happening?
Salesforce has updated its OAuth security requirements for connected apps. You can read Salesforce's full announcement here: Mandatory Security Updates for Connected Apps.
Qlik Automate has updated the Salesforce connector to comply with these new security requirements. However, because of the nature of this change, existing connections cannot be migrated automatically.
What action do I need to take?
Follow these steps after the release on Tuesday, the 5th of May:
- Open your Salesforce connection settings, navigate to the Salesforce connection in Qlik Automations, and open its configuration.
- Add your domain. In the connection settings, locate the Enhanced_domain field (an existing input field) and enter your Salesforce org's custom domain.
Make sure to include the "my" suffix if your domain has it. By using this, the 'environment' input is ignored.
Format: https://{enhanced_domain}.salesforce.com.
If you're unsure of your domain, you can find it in your Salesforce org under Setup → My Domain. - Re-authenticate. Once your domain is entered, you'll be prompted to log in to Salesforce again and authorize the updated app. Complete the login flow to re-establish the connection.
- Verify the connection. Run a test automation that uses the Salesforce connection to confirm everything is working correctly.
What happens if I don't act?
If you don't complete these steps after the release date, your Salesforce automations will stop working and return a 401 Unauthorized error. No data will be lost, but you will need to complete the steps above to restore access.
If you have any questions, we're happy to assist. Reply to this blog post or take your queries to our Support Chat.
Thank you for choosing Qlik,
Qlik Support - Open your Salesforce connection settings, navigate to the Salesforce connection in Qlik Automations, and open its configuration.
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Qlik Learning is now available in French!
We’re excited to announce a major step forward in making Qlik Learning more accessible, personalized, and impactful; translations are now available for all users. Our first stop is France. Guess where we are going next?
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From Dashboards to Decisions: What the Agentic Era Means for LATAM Universities
Something quietly remarkable happened in the first quarter of 2026. While the public conversation was still asking whether AI agents would really change business, Gartner reported that 40% of enterprise applications are expected to integrate task-specific AI agents by the end of 2026, up from less than 5% a year ago. G2's August 2025 survey of enterprise buyers found that 57% of companies already had AI agents in production, not a... Show MoreSomething quietly remarkable happened in the first quarter of 2026. While the public conversation was still asking whether AI agents would really change business, Gartner reported that 40% of enterprise applications are expected to integrate task-specific AI agents by the end of 2026, up from less than 5% a year ago. G2's August 2025 survey of enterprise buyers found that 57% of companies already had AI agents in production, not as chatbots, but as autonomous systems executing workflows, monitoring compliance, and coordinating decisions across business functions.
For those of us who work at the intersection of data, analytics, and higher education, this isn't a distant trend. It's a curriculum question.
The shift is not from manual to automated. It's from tools to teammates.
For two decades, the defining promise of business intelligence has been "self-service analytics", empower every user to query, visualize, and explore data themselves. In the agentic era, the paradigm changes. AI agents are not a new tool in the analyst's toolkit; they are analysts. They plan multi-step tasks, call APIs, reason across data sources, and increasingly execute actions without waiting for a human prompt.
At Qlik Connect 2026, the message was direct: enterprises are closer to agentic AI than they think, because the foundation they already built, governed data, trusted metrics, clear business logic — is exactly what agents need to operate reliably. In February, the general availability of Qlik's Model Context Protocol (MCP) Server made it possible for third-party assistants, including Anthropic's Claude and OpenAI's ChatGPT, to access governed enterprise data through Qlik's APIs rather than scraping dashboards. The dashboard is no longer the endpoint. It's one of many surfaces where a decision gets made.
The new skills gap is not technical. It's architectural.
Here is the uncomfortable reality: Gartner projects that over 40% of agentic AI projects will fail by 2027, not because the models aren't capable, but because legacy systems, poor data architectures, and weak governance can't support autonomous execution. Deloitte's 2026 State of AI in the Enterprise report, based on a survey of 3,235 leaders across 24 countries, found that only 25% of organizations have moved 40% or more of their AI pilots into production, and just 21% have a mature governance model for autonomous AI agents.
The scarce capability is no longer "who can build a dashboard." It is:
- Who can design a KPI dictionary an agent can trust?
- Who understands bounded autonomy, where humans set the rules and agents execute within them?
- Who can distinguish explainable reasoning from confident hallucination?
- Who can architect a data product that an agent can consume without a human in the middle?
These are not niche skills reserved for data engineers. They are the new baseline for anyone graduating into a workforce where, by 2028, Gartner estimates 15% of day-to-day decisions will be made autonomously.
The LATAM opportunity
This is where Latin America has a genuine strategic window. Our universities often face the critique of "catching up" on technology adoption. In the agentic era, that framing is misleading, the agentic shift resets the starting line for everyone. Institutions, anywhere in the world, that graduate students fluent in data governance, explainable AI, and human-agent collaboration will be the ones supplying the talent that enterprises are already scrambling to hire.
According to DataCamp's 2026 State of Data & AI Literacy Report, 88% of enterprise leaders say basic data literacy is important for day-to-day work, 60% report a data skills gap in their organization, and organizations with mature literacy programs are nearly twice as likely to see strong AI returns. The companies that will hire our graduates next year are telling us, in plain terms, what they need.
What universities can do now
Three practical moves that don't require launching a new degree program:
- Teach governance alongside analytics. Every data course should include a module on trust, lineage, and explainability, not as an afterthought, but as the foundation that makes agents usable.
- Shift from tool training to platform fluency. Students don't need to master one vendor; they need to understand how governed data, semantic layers, and agent orchestration fit together.
- Build industry-embedded learning paths. Programs like the Qlik Academic Program exist precisely because real agentic work happens on real data with real stakes. Classroom theory is not enough.
The agentic era will not be defined by which models win. It will be defined by which people, and which regions,learned to work alongside them first.
By giving students, professors, and universities free access to analytics software, learning content, and certifications, the Qlik Academic Program helps education stay aligned with the data trends shaping 2026 and prepares learners for the jobs of tomorrow.
Join our global community for free: Qlik Academic Program: Creating a Data-Literate World
