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Recent Blog Posts

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    Support Updates

    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... Show More
    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=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

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    Design

    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 buil... Show More

    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.

    structure.png

     

     

     

     

     

     

     

     

     

     

     

    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.

    excel3.png

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

     

    • 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.

    script2.png

     

    Here is a view of the layout table with the new fields that were created in the script.

    complete layout table.png

     

    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.

    mBar.png

     


    mStart is the starting position of the bar in the waterfall chart and for subtotals, this is always 0.

    mStart.png

     


    mMax is the max bar length which is used to scale the bars in the waterfall chart.

    mMax.png

     

    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:

    1. A plain line with an offset
    2. A thin gray line where x=0
    3. A label

    inline svg.png

     

    • 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:

    final.png

     

    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.

    rowstyle.png

     

     

    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.

    indent.png

     

    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.

    blank.png

     

    The chart column representation is set to Image in the properties of the straight table.

    image.png

     

     

    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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    Explore Qlik Gallery

    Color Palette

      Color Palette Nitin This Dashboard defines a set of predefined colors used to help maintain consistency and clarity across the dashboard, it... Show More
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    blog

    Explore Qlik Gallery

    Knowledge Nuggets 2026(Q1)

    Knowledge Nuggets - 2026(Q1) Insight Consulting A collection of Qlik and Data & AI Literacy related videos and articles Discoveries Contri... Show More
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    Support Updates

    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 ... Show More

    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, 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:

     

    Thank you for choosing Qlik,
    Qlik Support

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    Support Updates

    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 ins... Show More

    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 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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    Design

    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 reporti... Show More

    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 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.

    Exec Summary.png

     

    The P&L sheet provides a more detailed look at profit and loss.

    PandL.png

     

    The Cost Center sheet uses the pivot table to show sales costs.

    Cost Center.png

     

    Find a detailed look of cash flow on the Cash Flow sheet.

    Cash Flow.png

     

    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 (QVF) here.

    Thanks,

    Jennell

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    Design

    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 t... Show More

    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 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#/ 

    Screenshot 2026-04-24 at 7.11.24 AM.png

    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.

    Screenshot 2026-04-24 at 7.13.20 AM.png

    Screenshot 2026-04-24 at 7.13.38 AM.png

     

    • 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.

    Screenshot 2026-04-24 at 7.16.20 AM.png

     

    • Leaderboard: As real matches get played in June and July, submitted brackets are scored automatically and players are ranked in the leaderboard table.

    Screenshot 2026-04-24 at 7.18.31 AM.png

     

    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.

    Screenshot 2026-04-24 at 12.15.23 AM.png

    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:

    1. elo_diff
    2. rank_diff
    3. is_neutral
    4. h2h_team_a_advantage
      etc...

    Screenshot 2026-04-24 at 12.43.16 AM.png

     

    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).

    Screenshot 2026-04-24 at 7.35.44 AM.png

    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.

    Screenshot 2026-04-24 at 7.53.56 AM.png

     

    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!

    Go fill out your bracket

    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!

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    Support Updates

    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 Qli... Show More

    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 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:

    1. Open your Salesforce connection settings, navigate to the Salesforce connection in Qlik Automations, and open its configuration.

    2. 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.


    3. 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.

    4. 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

     

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    Qlik Learning

    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 availab... Show More

    French-Announcement.png

     

     

    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. 

    Your feedback drives this launch. One of your top requests was learning in your preferred language, and today we’re making that happen. 

    To accelerate availability, we’re leveraging machine learning–based translation technology to quickly bring essential content to more learners around the world. We’re kicking things off with our first set of courses in French, followed by Japanese, Italian, and many more languages coming soon. 

    🌐 Getting Started 
    Changing your language is simple: 

    • Select your preferred language from the option at the bottom of any Qlik Learning page. Bilge_Kara_2-1776964565454.png

       

       

     

    ⚠️ What to Expect 

    • Not all content is currently available in every language.  
    • The Topics menu displays only content available in your selected language.  
    • As a result, English content may appear more comprehensive at this time.  
    • We are actively expanding and enhancing translated content across the platform.  
    • Translations will continue to improve as we refine quality and address remaining gaps.  

     

    🛠️ Additional Notes 

    • Machine translations may vary in accuracy and should not be considered fully definitive.  
    • To maintain consistency across, certain terms remain untranslated (for example, product names, Qlik-specific terminology, and syntax).  

     

    We truly appreciate your feedback and patience as we continue to evolve. To provide feedback, click the stars 

    Bilge_Kara_0-1776964334351.pngat the top of this page and share your feedback with us.

     

    We hope you enjoy Qlik Learning in the language that works best for you! 

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    Qlik Academic Program

    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 w... Show More

    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 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:

    1. 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.
    2. 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.
    3. 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

     
     
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    Japan

    【オンデマンド配信】Qlik 金融事例のご紹介

    デジタル化の加速と競争激化により、金融機関を取り巻く市場環境は大きく変化しています。顧客期待の高度化、行動のデジタルシフト、情報の半減期の短縮化。これらの変化に対し、世界の金融機関はどう動いたのか。Qlik のグローバル金融事例を分析すると、「データの信頼性・鮮度・活用の自律性」という 3 つの共通... Show More

    デジタル化の加速と競争激化により、金融機関を取り巻く市場環境は大きく変化しています。顧客期待の高度化、行動のデジタルシフト、情報の半減期の短縮化。これらの変化に対し、世界の金融機関はどう動いたのか。Qlik のグローバル金融事例を分析すると、「データの信頼性・鮮度・活用の自律性」という 3 つの共通条件が浮かび上がります。
    本 Web セミナーでは、データを通じた代替不可能な顧客との信頼をどう築くか。具体的な事例とともにお伝えします。

    ※ パソコン・タブレット・スマートフォンで、どこからでもご参加・ご視聴いただけます。

    今すぐ視聴する

    FY26Q2_IWS_Banking_blog.jpg

    今すぐ視聴する

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    Design

    Enhancing the multilingual experience with automatic locale detection

    Introduction In our increasingly globalized environment, enabling seamless multilingual support in your Qlik Sense apps is no longer a nice-to-have - ... Show More

    Introduction

    In our increasingly globalized environment, enabling seamless multilingual support in your Qlik Sense apps is no longer a nice-to-have - it’s expected.

    Many implementations require users to manually select their desired language to display labels and content. In a helpful Qlik Community post, Jennel guides users through building a multilingual Qlik Sense app using an Excel-based translation table and manual language selection via dropdowns.

    While Jennel’s solution is powerful and flexible, it relies on users making that initial language choice. In this article, I’ll show how to streamline the user experience by automatically detecting a user’s preferred language - based on their Qlik Cloud profile - and dynamically adapting the app accordingly using the GetUserAttr('userLocale') function.

     

    How Jennel’s Approach Works

    Jennel’s method involves:

    • Preparing an external source (e.g., an Excel file) that stores translations for labels and interface elements.
    • Loading this translation table into the app.
    • Letting users manually switch languages using a selection control such as a filter pane.
    • Using conditional expressions in the UI to swap labels and dimensional headings based on the selected language.

    This approach, while widely used, introduces a required step - it depends on users selecting their preferred language every time they open the app.

     

    Enhancing the Experience with Automatic Locale Detection

    My solution builds on Jennel’s foundation with one key improvement: the app automatically reads the user’s preferred language from their Qlik Cloud settings via the newly added attribute to the GetUserAttr: userLocale. This eliminates manual language selection and delivers an interface that adapts instantly and seamlessly to each user.

     

    Technical Breakdown

    In the Data Load script, nothing really changes from Jennel’s approach: I loaded an external file containing the required translations:

    Picture1.png

    The magic happens in the front-end part of the analytics app. Everything that should be translated uses the same approach that Jennel stated in her article: a variable with a Set Analysis filter containing the ID of that specific label/title/subtitle.

    ={<Index={46}>} $(vLanguageString)

    The magic is in the variable; $(vLanguageString), in fact, is defined as:

    Alberto_Vaghi_1-1757015347543.png

    vLanguageString = Only({<Language={"$(vUserLanguage)"}>} Translation)

    Please note the use of another variable called “vUserLanguage”: the usage of a nested variable allows to manage situations in which the user locale is not included in the translations table. Let’s say a user has Qlik Cloud set in Spanish but Spanish translations are not available: in this case the app would display everything in English despite the user locale selection.

    The variable “vUserLanguage” is defined as follows:

    Alberto_Vaghi_2-1757015357723.png

    vUserLanguage = if(count({<Lang={"$(=GetUserAttr('userLocale'))"}>} Lang) = 0, 'en', GetUserAttr('userLocale'))

    As you can see, I used GetUserAttr(‘userLocale’) to fetch the preferred language set by the user in their Qlik Cloud profile. Doing this, automatically sets the translation to the user’s preference without any manual intervention.

    The field “Lang” is in a dedicated table I created in the Load Script that contains all the languages available in the translations table:

    Alberto_Vaghi_4-1757015380726.png

    To give users feedback regarding the current language, I used a flag image conditionally displayed in the app by leveraging a Layout Container. Layout Container, in fact, can conditionally display elements inside them: I then defined the conditional display rule as follows.

    =$(vUserLanguage) = 'de' for German Flag

    =$(vUserLanguage) = 'en' for English Flag

    =$(vUserLanguage) = 'it' for Italian flag

    An alternative solution could be to use a KPI with a conditional background image, using the string returned by GetUserAttr as part of the image name. Note that I used the “vUserLanguage” variable to ensure that we catch the default in case user locale is not available in the translations table.

     

    The result

    Accessing the app with locale set to “English” displays all labels and titles in English:

    Alberto_Vaghi_5-1757015453786.png

    Let’s go to my Qlik Cloud profile and changing locale to “Italian”:

    Alberto_Vaghi_6-1757015464198.png

    Re-accessing the app displays labels and titles in Italian (check the flag on top right!):

    Alberto_Vaghi_7-1757015522396.png

    Easy, without any additional effort!

    Hope this article inspires you to build multilingual apps with this new feature!

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    Support Updates

    Upcoming deprecation of Qlik Analytics charts in May 2027

    Qlik constantly refines its Analytics, over time replacing old charts with new, modernized alternatives. These deprecations are announced well in adva... Show More

    Qlik constantly refines its Analytics, over time replacing old charts with new, modernized alternatives. These deprecations are announced well in advance and come with instructions on how to best replace these old charts, whether that is to use a new one, several new ones, or make use of new settings.

    This blog post covers the deprecation of charts in May 2027 and offers you guidance on how to replace them.

     

    What charts are being deprecated and when?

    The following seven visualization bundle charts are up for deprecation in May 2027. Most have already been removed from the asset panel and are no longer a part of recent applications.

    • The Bar and Area chart
    • The old Bullet chart
    • The old Heatmap chart
    • The Button for navigation
    • The Share button
    • The Show/Hide container
    • The old Tabbed container
    • The Multi KPI

     

    What do I use instead?

    Since these are old charts, most are no longer in use. If you happen to still have a very old application and need to replace deprecated charts, see Visualization bundle > Deprecated charts for more information on what to use instead.

     

    How do I find out if my apps are using the deprecated charts?

    Qlik recommends reviewing your apps for old charts. Depending on your platform (Qlik Cloud or Client-managed), there are different methods you can deploy.

     

    Qlik Cloud

    Qlik Cloud administrators should use the Qlik Cloud Monitoring Apps to track the usage. The App Analyzer has a sheet dedicated to where deprecated charts are being used on a tenant in Qlik Cloud. The App Analyzer is based on usage events rather than scanning every app. Use the App Analyzer to find which apps and sheets have charts that need to be updated to newer and more modern alternatives. The easiest way to install and update the Qlik Cloud Monitoring Apps is to use the automation template. If you already have the App Analyzer, just remove the automation and install a new one to get the latest version of the App Analyzer. 

     

    Client-managed

    For client-managed installations, use the Monitoring apps. The Content Monitor app has a sheet for tracking deprecated charts. At reload, the Content Monitor app scans every app in the installation in order to list all applications and sheets that are using charts that are being deprecated. It also lists the installed extensions and their deprecation status. The Monitoring apps are bundled with the Qlik Analytics installation. The first version with the new sheet will be included in the May 2026 release. If you want to track usage in prior versions, the deprecated chart usage scanner will also be available on the product download page.

     

    Thank you for choosing Qlik,
    Qlik Support

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    Support Updates

    Qlik Answers is now even faster

    We've made an update to Qlik Answers that delivers faster responses to your questions. See What's New in Qlik Cloud for the announcement.   What chang... Show More

    We've made an update to Qlik Answers that delivers faster responses to your questions. See What's New in Qlik Cloud for the announcement.

     

    What changed

    The Data Analyst Agent in Qlik Answers now handles semantic search, expression building, and chart generation within a single, unified flow. When you ask a question, the Answers Agent and the Data Analyst Agent work together to deliver your response, and you'll see both reflected in the interface as Qlik Answers responds.

    The practical effect: Qlik Answers can take your question, figure out what to search for, build the right expression, and generate the right visualization in a single connected process rather than as separate steps. Complex questions, the kind that involve comparisons across dimensions, multiple measures, or specific time periods, benefit the most because the agent can hold the full shape of your question in mind while deciding how to answer it.

     

    See it in action

    Here's an example of how the same question flows through Qlik Answers. Previously, the response involved several specialized agents handing work back and forth. With the updated architecture, the question is resolved through a more direct flow, and you'll see the response come back faster.

     

    before and after.png

    Try it yourself! Ask any question you often repeat, especially one with comparisons or multiple parts. You'll notice Qlik Answers gets to the response faster.

     

    What this means for you

    You will see the difference the next time you open Qlik Answers, but everything else you rely on in Qlik Answers (your data, your spaces, your permissions, or the way you ask questions) will continue to work exactly as it did before the update went live.

     

    What's next

    We'll continue to evolve how the agents work as we add new capabilities, and we'll keep sharing what's changing along the way.

    We'd love to hear how the updated experience feels in your day-to-day use. Reach out to your Qlik contact or share your thoughts in the community.

     

    Thank you for choosing Qlik,
    Qlik Support

     

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    Qlik Academic Program

    Welcome Back Katherine Taylor Pearson – Qlik Educator Ambassador for 2026!

    The Inspiration Behind Using Qlik As a nurse informaticist and educator, Katherine has always been passionate about bridging the gap between data anal... Show More
    The Inspiration Behind Using Qlik
    As a nurse informaticist and educator, Katherine has always been passionate about bridging the gap between data analysis and patient-centered care. Qlik’s intuitive interface and strong analytics capabilities make it an ideal tool for teaching students how to visualize, interpret, and communicate healthcare data effectively. By working with real-world datasets and applied scenarios, students develop the analytical thinking and problem-solving skills needed in today’s healthcare environment.
     
    Integrating Qlik into the Classroom
    Qlik has become an important part of Katherine’s teaching strategy through active, hands-on exercises that allow students to analyze healthcare trends, public health indicators, and social determinants of health. Students engage with dashboards, explore datasets, and learn how analytics can inform better care delivery, workflow improvement, and population health decision-making. She also encourages students to explore Qlik training opportunities and certifications, helping them build marketable skills that strengthen their confidence and career readiness.
     
    Real-World Impact: Internships and Job Opportunities
    Many of Katherine’s students have successfully used their Qlik experience to pursue internships, practicum opportunities, and careers in healthcare analytics, informatics, quality improvement, and hospital operations. Employers increasingly value graduates who can translate raw data into clear, actionable visualizations, and Qlik gives students a skill set that aligns well with workforce needs in a data-driven healthcare landscape.
     
    Classroom Goals for the Year Ahead
    Looking ahead, Katherine is focused on expanding student engagement through even more immersive and innovative analytics experiences. In addition to continuing work in AI-driven analytics, predictive thinking, and data storytelling, she is planning a datathon that will challenge students to collaborate, analyze data, and generate solutions to real healthcare and public health problems. She is also launching a Public Health Data Forum Simulation, an interactive learning experience designed to help students interpret public health data, discuss findings with stakeholders, and make informed recommendations in a simulated decision-making environment.
    These initiatives are intended to strengthen students’ confidence, communication skills, and ability to apply analytics in realistic healthcare and public health settings.
     
    Industry Trends and the Future of Analytics in Education
    Healthcare continues to become more data-driven, with AI, machine learning, predictive analytics, and real-time data sharing playing increasingly important roles in clinical, operational, and public health decision-making. At the same time, higher education is placing greater emphasis on applied learning experiences that prepare students not only to understand data, but also to use it in meaningful, ethical, and practice-focused ways. Katherine believes that providing students with practical analytics experience is essential to preparing the next generation of nurse leaders and informatics professionals.
     
    Life Beyond Teaching
    Outside the classroom, Katherine enjoys staying active through swimming, running, and yoga. She also loves spending time outdoors with her family and their Siberian Husky. Based in Texas, she remains deeply committed to advancing nursing informatics, public health, and data-informed education.
     
    Looking Forward as an Educator Ambassador
    As an Educator Ambassador, Katherine is excited to continue collaborating with fellow educators, exploring innovative teaching strategies, and creating new ways to engage students with data analytics. She looks forward to sharing insights from her work in nursing and public health informatics, including her datathon and Public Health Data Forum Simulation initiatives, while continuing to grow as an educator and advocate for data-informed learning.
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    Japan

    【申し込み開始!】6/10(水)開催:AI Reality Tour Tokyo 2026

    AI Reality Tour Tokyo 2026:Qlik でデータを AI の原動力へ 来たる 6/10(水)、「AI Reality Tour Tokyo 2026」を開催いたします。 AI は急速に進化しています。その一方で、AI がもたらす価値でビジネス成果を実現している企業は、わずか... Show More

    AIRT2026_Blog.jpg

    AI Reality Tour Tokyo 2026:Qlik でデータを AI の原動力へ

    来たる 6/10(水)、「AI Reality Tour Tokyo 2026」を開催いたします。

    AI は急速に進化しています。その一方で、AI がもたらす価値でビジネス成果を実現している企業は、わずか 5% だという調査結果があります。最大の障壁となっているのは、AI モデルではありません。主な障壁は、データの品質・可用性・アクセス性・既存システムとの統合・ガバナンス・セキュリティなど、データやシステムであることが明らかになっています。先進的な企業では、あらゆる AI 戦略を最大化するために、単に最新のモデルを追求するだけでなく、「信頼できるデータ基盤」の構築に投資しています 。

    AI がもたらす価値と現実とのギャップを解消するには?本イベントでは、AI を実現・加速・適応する最先端のソリューションをご紹介します。

    •  Qlik の AI ビジョンと戦略 - 企業全体の AI 活用を成功に導く実践的な手法
    •  最新のエージェンティック - 今すぐ活用できる最新のイノベーションが切り拓く新たな可能性
    •  先進的な顧客事例 - Qlik を活用してビジネス変革を実現している企業の事例
    •  新たなつながり - 新たな知見をもたらす Qlik のエキスパートや同業他社との交流

     

    Qlik のエキスパートによる基調講演、Qlik ユーザーの先進的な事例、Qlik 技術部門による最新の製品情報、Qlik のパートナー企業による最新のソリューションや展示ブースなどを予定しています。また、イベントの最後には、データのスペシャリスト同士の交流をお楽しみください。

    お申し込みの締め切りは、6月 2日(火)17:00 までです。お早めにお申し込みください。

    今すぐ申し込む

    【開催概要】

    日時:
    2026年 6月 10日(水)13:00 - 18:30(受付開始 12:00)
                                                     懇親会 18:30 - 19:30
    会場:
    有明セントラルタワーホール&カンファレンス
              東京都江東区有明3-7-18 有明セントラルタワー3F・4F

    参加費:無料
    お問い合わせMarketingjp@qlik.com までお問い合わせください。

    今すぐ申し込む

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    Design

    Qlik Cloud Monitoring Apps - App Analyzer Update - Session Level Data

    The latest update to the App Analyzer brings a new feature: session-level data. Now, the App Analyzer can answer vital questions, such as which users ... Show More

    The latest update to the App Analyzer brings a new feature: session-level data. Now, the App Analyzer can answer vital questions, such as which users are accessing which applications, how long they stay in each app, what sheets they use, the duration on each sheet, and the frequency of navigation between sheets. It also tracks the number of concurrent users within an app or across all apps in the tenant. The App Analyzer is released and updated by Master Principal Analytics Architect @Daniel_Pilla. He will monitor this thread should you have any questions. 

    In summary the App Analyzer’s key benefits include maintaining app size quotas, tracking user adoption, optimizing data models, and now analyzing user and session-level behavior.

    The app analyzer can be easily programmatically installed along with all of the other monitoring apps via an out of the box Qlik Application Automation template. Please visit the links below for more information and to get started using it. 

    Resources: 

     

     

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    Support Updates

    Qlik Stitch: Upcoming HubSpot API Changes effective April 30th 2026

    Hello Sitch users,   Starting April 30, 2026, all but three HubSpot Contact Lists API endpoints will be removed and return errors. Some Contact API en... Show More

    Hello Sitch users,

     

    Starting April 30, 2026, all but three HubSpot Contact Lists API endpoints will be removed and return errors. Some Contact API endpoints will also be impacted. Details on affected endpoints can be found in Contact Lists API (v1) sunset moved to April 30, 2026 | hubspot.com.


    What does it mean for Qlik Stitch HubSpot connector users?

    To avoid any failures or data loss, all Qlik Stitch users are required to migrate their tasks to the latest HubSpot V4 version before April 30. All previous versions (v1, v2, v3) will no longer be supported.

     

     

    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

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    Qlik Academic Program

    Welcome, Qlik Academic Program Educator Ambassador 2026: Manikant Roy!

    I feel pleased to introduce Manikant Roy, Assistant Professor, Business Analytics at the Jaipuria Institute of Management in Noida, India. Manikant’s ... Show More

    I feel pleased to introduce Manikant Roy, Assistant Professor, Business Analytics at the Jaipuria Institute of Management in Noida, India.

    Manikant’s journey with Qlik began long before he entered the academia world. It was at the start of his professional career in 2012 as a Business Intelligence Consultant that he worked extensively as a developer using QlikView. This early exposure to analytics and data visualization helped him understand the importance of data-driven decision-making in organizations.

    In 2016, he became associated with the Qlik Academic Program through interactions with Qlik Academic Program Manager, Pankaj Muthe. That connection encouraged him to bring Qlik technologies into the academic environment, and since then he has actively advocated the use of analytics and data literacy in higher education.

    Over the years, Manikant has incorporated both QlikView and Qlik Sense into his teaching. He developed semester-long courses for MBA, MSc, and BTech students covering areas such as Business Analytics, Data Visualization, and Business Intelligence. His teaching approach follows a progressive learning path where students begin with Qlik Data Literacy concepts, then move into Qlik Data Analytics fundamentals, and finally applied these concepts using Qlik Sense for business analysis and dashboard development.

    Through this hands-on approach, students learn how to visualize data effectively, communicate insights, and make data-informed decisions. They use Qlik tools to develop dashboards, analyze real-world datasets, and complete academic projects and master’s dissertations. To date, he has trained more than 400 students in analytics and data visualization using Qlik technologies.

    The impact of this learning has been very encouraging. Many students have secured internships and full-time roles in analytics and technology domains after learning these skills. Several alumni have progressed into senior technical positions in the industry, including technical leadership roles. One example is Anurag Chaudhary, a former student who is now working as a Tech Lead in a leading organisation. Such success stories highlight the importance of strong analytics education and practical exposure to modern BI tools.

    Beyond the classroom, Manikant has actively conducted workshops, faculty development programs, and mentoring sessions across various colleges and universities in India. He regularly speaks about Business Intelligence and analytics using Qlik technologies at student events, hackathons, and academic forums. These engagements help students and educators understand how analytics tools can be applied to solve real-world business challenges.

    At Jaipuria Institute of Management, Qlik technologies are integrated into the Business Analytics curriculum as an essential component of classroom learning. He encourages students to pursue certifications offered through the Qlik Academic Program, and more than 30 students from the institute have already completed certifications in Data Literacy and Data Analytics.

    Looking ahead to 2026, Manikant’s goal is to further strengthen students’ ability to work with data and apply analytics concepts to real-world scenarios. The world today is more dynamic than ever before, and continuous learning is the key to staying relevant. By engaging students in practical analytics projects, real datasets, and professional certifications, his aim is to help them build the confidence and skills required to thrive in the data-driven economy.

    From his perspective, being data-driven—both personally and professionally—is no longer a luxury but a necessity. With the rapid advancement of artificial intelligence and analytics technologies, organizations are increasingly relying on data to guide decisions. Manikant further adds, “Students must learn how to read, interpret, and communicate insights from data. Developing the ability to “read, write, and argue with data” is an essential skill for the next generation of professionals”

    On a personal note, Manikant lives in Noida in the Delhi NCR region of India. He often says that he is a teacher by choice, not by chance. Over the years, he has mentored students from diverse backgrounds, helping them develop skills and prepare for careers in analytics and technology. Manikant strongly believes that education is one of the most meaningful ways to uplift individuals and contribute to society.

    In addition to his academic work, he has been involved in mentoring initiatives for young learners. Manikant has been recognized as a “Gems of Mentor India” by the Atal Innovation Mission under NITI Aayog for mentoring school students and encouraging them to develop digital and innovation skills aligned with the vision of Viksit Bharat 2047.

    Outside the classroom, he enjoys gardening and reading classical literature. Manikant is particularly interested in philosophical reflections about life and society. Whenever possible, he enjoys taking long drives with school friends on weekends, which gives him time to reflect and reconnect.

    Manikant says, “I feel truly honored to be recognized as a Qlik Educator Ambassador after many years of advocating analytics education. Through this role, I look forward to connecting with educators across the world, learning from global best practices, and contributing to the promotion of data literacy. Empowering people with the ability to understand and use data is one of the most important educational missions of our time”

    We welcome Manikant to the Educator Ambassador Class of 2026 and wish him all the best.

    To know more about Educator Ambassadors, you could visit: https://www.qlik.com/us/company/academic-program/ambassadors

    To learn more about the Qlik Academic Program, you could visit: qlik.com/academicprogram

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