Unlock a world of possibilities! Login now and discover the exclusive benefits awaiting you.
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
-
Knowledge Nuggets-2026Q3
Knowledge Nuggets-2026Q3Insight ConsultingA collection of Qlik and Data & AI Literacy related videos and articles, updated to Sept 2026DiscoveriesContributor and Keywords frequencyImpactLearning resourceAudienceAll Qlik stakeholdersData and advanced analyticsLearning resource -
ODBC Connector for Qlik Sense Enterprise on Windows: Upcoming End of Support for...
Effective in the Qlik Sense Enterprise on Windows November 2026 release, and in the latest patches for May 2025, November 2025, and May 2026, the ODBC connector used by Qlik Sense Enterprise on Windows will no longer support connections secured with TLS 1.0 or TLS 1.1. To maintain uninterrupted connectivity, customers should upgrade their environments to use TLS 1.2 or higher ahead of applying these releases or patches. Refer to the release notes... Show MoreEffective in the Qlik Sense Enterprise on Windows November 2026 release, and in the latest patches for May 2025, November 2025, and May 2026, the ODBC connector used by Qlik Sense Enterprise on Windows will no longer support connections secured with TLS 1.0 or TLS 1.1. To maintain uninterrupted connectivity, customers should upgrade their environments to use TLS 1.2 or higher ahead of applying these releases or patches.
Refer to the release notes upon release of the affected versions for details.
Why is this happening?
TLS 1.0 and TLS 1.1 are legacy encryption protocols that are no longer considered secure and have been deprecated across the industry for several years. Removing support for these older protocols in the ODBC connector aligns Qlik's connectivity stack with current security standards and reduces exposure to known vulnerabilities in outdated TLS implementations.
Who is affected?
This change affects the ODBC connector in Qlik Sense Enterprise on Windows only. At this point, Qlik Sense Desktop and QlikView are not affected by this change.
Any data source connection made through the ODBC connector in Qlik Sense Enterprise on Windows that relies on TLS 1.0 or TLS 1.1 will be affected once support is removed, regardless of whether the TLS version is enforced by the data source itself, a network intermediary, or the client driver configuration.
What does this mean for me?
If your data source, ODBC driver, or the underlying operating system is currently configured to negotiate connections using only TLS 1.0 or TLS 1.1, those connections will fail once you move to a version of Qlik Sense Enterprise on Windows that removes TLS 1.0 or TLS 1.1 support.
Reload tasks, extensions, and any other workflows using affected ODBC connections will no longer be able to connect to the data source.
What should I do?
- Review and upgrade your environment so that all ODBC connections negotiate TLS 1.2 or greater before you upgrade Qlik Sense Enterprise on Windows.
- If you are not already using TLS 1.2 or later, recreate the connection with the updated TLS configuration.
Questions?If you have questions or need assistance planning your upgrade, our forums are open to you, and Support is only a chat away.
Thank you for choosing Qlik,
Qlik Support -
Qlik Open Lakehouse on Google Cloud Platform
Private Preview · Google Cloud Qlik Open Lakehouse comes to Google Cloud Sign up for the Private Preview and get hands-on with real-time Iceberg tables in your own Google Cloud project — no lock-in, no re-architecting. Sign up for the Private Preview! If you're running analytics on Google Cloud, you already know the tension. BigQuery is fast and familiar, but the more data you pour into it, the more your ingestion and storage bill climbs, and ... Show MorePrivate Preview · Google CloudQlik Open Lakehouse comes to Google Cloud
Sign up for the Private Preview and get hands-on with real-time Iceberg tables in your own Google Cloud project — no lock-in, no re-architecting.
If you're running analytics on Google Cloud, you already know the tension. BigQuery is fast and familiar, but the more data you pour into it, the more your ingestion and storage bill climbs, and the more your data ends up shaped around one engine. You want the performance without the lock-in, you want your data to stay yours, and you want to free up some budget for more valuable workloads.
That's exactly the problem Qlik Open Lakehouse solves — and we're getting ready to launch a Private Preview on Google Cloud this September that you can be part of.
Qlik Open Lakehouse gives you a fully managed way to ingest real-time data straight into Apache Iceberg tables that live in your own Google Cloud Storage buckets. No proprietary formats, no copies, no re-architecting your data layer. Query those same tables from BigQuery, Trino, or any Iceberg-compatible engine, and pay a fraction of what you'd normally spend moving and storing that data.
If you've followed our work on AWS, this will feel familiar — and that's the point. We're porting a proven architecture to Google Cloud, not building a science experiment.
How it works: a walk through the architecture
Open Lakehouse builds the bronze layer of your medallion architecture, ingesting and landing real-time data as optimized Apache Iceberg tables, with the heavy lifting executed in your own Google Cloud project. From there, push-down transformations in Qlik Talend® Cloud pipelines create your silver and gold layers directly on BigQuery. Here's the path your data takes, stage by stage.
1 · Ingestion at the edge
Your sources land through two paths. For change data capture and bulk loads from databases, SAP, and mainframe systems, the Qlik Data Movement Gateway sits in your managed environment and handles CDC and bulk ingestion. For streaming and event data, you connect Kafka topics or Google Cloud Storage directly. Both routes feed the landing stage without your data ever leaving your control. Later in the Private Preview, we'll also add support for Qlik Replicate as a source, so if you're already a Replicate customer, you can onboard data from your existing CDC sources into Iceberg without migrating a single pipeline or switching tools.
2 · Compute in your project
Two components run on Google Compute Engine inside your environment. The Network Integration Agent runs on a standard Compute Engine VM and brokers secure connectivity between the Qlik Talend Cloud tenant and your resources. The Open Lakehouse Cluster — the engine that writes and optimizes your Iceberg tables — runs on a Compute Engine managed instance group built on Spot VMs. That Spot-based design is deliberate: it's where a large part of the cost savings comes from, because you're running the ingestion and optimization workload on Google Cloud's most cost-efficient compute instead of always-on, premium-priced infrastructure.
3 · Open storage you own
Everything lands in Google Cloud Storage, split across a landing bucket for incoming data, a config bucket for pipeline metadata, and table storage where your data comes to rest as Apache Iceberg tables. These buckets are in your account. The data is written in an open table format from the start, so there's never a moment where it's trapped in something only Qlik can read.
4 · A catalog any engine can use
Iceberg tables are registered in the Google Lakehouse runtime catalog, so your tables are discoverable and governable through Google Cloud's native catalog rather than a Qlik-proprietary one. That's what makes zero-copy querying real: BigQuery reads the same tables through ELT, and so can Trino or any other Iceberg-compatible engine, all pointing at one physical copy of the data.
5 · A managed bronze layer, ready to build on
The pipeline moves through managed stages — landing, storage, and mirror — to produce clean, governed Iceberg tables without you hand-coding each hop. You get Type 1 and Type 2 slowly changing dimensions or append-only patterns out of the box, so history and current-state tables are handled for you. We'll also add zero-copy mirroring to BigQuery during the Private Preview, so you can surface your Iceberg data straight in BigQuery. If you want to replace an existing native table, you can, since downstream queries keep working exactly as before.
The result: real-time data flows from your sources into governed, query-ready Iceberg tables in your own Google Cloud Storage, optimized continuously, queryable from BigQuery and beyond — and you never gave up control of a single byte.
Built on proven AWS foundations
We didn't start from zero for Google Cloud. Qlik Open Lakehouse first shipped on AWS, where it's already running these same patterns: CDC and streaming ingestion, Spot-based compute for cost-efficient optimization, Iceberg tables in customer-owned object storage, and open querying across engines.
Bringing it to Google Cloud is a deliberate step toward feature parity across clouds. The architecture mirrors what's proven on AWS, adapted to Google Cloud's building blocks: Compute Engine in place of EC2, Google Cloud Storage in place of S3, BigQuery and the Google Lakehouse runtime catalog as the native query and catalog layer. Same engine, same principles, GCP-native execution.
This matters because of what it says about our direction. We believe you should be free to choose where your data lives, which engine queries it, and to change your mind later without a migration project. Delivering the same open lakehouse capability across AWS and Google Cloud, with more to come, is how we make that freedom real rather than a slide in a pitch deck.
Why it matters
Everything above maps to three things we care about:
TRUSTBuild governed data products in Qlik Talend Cloud on top of your Iceberg tables. Your data stays in open Apache Iceberg format, in your own account.
FREEDOMQuery from BigQuery, Trino, or any Iceberg-compatible engine, and swap or add engines later without re-architecting. No lock-in to a single vendor or format.
COST OPTIMIZATIONSpot VM compute and zero-copy, single-storage architecture mean you spend far less to move and hold your data at scale.
Join the Private Preview
We're accepting participants now, and we're prioritizing organizations already standardized on Google Cloud and working with BigQuery or Apache Iceberg in their accounts.
Request your spot in the Private Preview →Opt in through the form and the Qlik team will reach out to schedule a welcome call. Already signed up? Sit tight — we'll be in touch.
-
Introducing the Region Mover capability in the Qlik Talend Cloud Migration Toolk...
The Region Mover, available with the Qlik Talend Cloud Migration Toolkit (QTCMT), enables users to migrate a Talend Cloud (TC) or Qlik Talend Cloud (QTC) tenant to another Qlik Talend Cloud tenant while either remaining on Talend 7 or upgrading to Talend 8. Before starting a migration, users can view the source tenant inventory directly in the Qlik Talend Cloud Migration Toolkit. This provides visibility into the currently existing assets and tho... Show MoreThe Region Mover, available with the Qlik Talend Cloud Migration Toolkit (QTCMT), enables users to migrate a Talend Cloud (TC) or Qlik Talend Cloud (QTC) tenant to another Qlik Talend Cloud tenant while either remaining on Talend 7 or upgrading to Talend 8.
Before starting a migration, users can view the source tenant inventory directly in the Qlik Talend Cloud Migration Toolkit. This provides visibility into the currently existing assets and those available for migration.
The migration is organized into three steps:- Administrative assets: Users, groups, projects, and user/group authorizations
- Talend projects: Package and push artifacts, upgrade code to Talend 8, generate CVE reports, and upload artifacts to Nexus 3 or JFrog Artifactory
- Runtime assets: Tasks, task artifacts, task parameters, task triggers, and plans
For questions or assistance, please contact Qlik Support.
Why Use Region Mover?
There are several scenarios where customers may need to move assets to a different region, including:
- A current region is no longer supported
- A move from Talend Cloud to Qlik Talend Cloud is required
- A newly available region was not previously an option and is now available
- Assets need to be consolidated from one tenant into an existing tenant
Region Mover enables faster migration, migrating assets to a new tenant more than 20x faster than performing the same migration manually, and significantly simplifies each migration step while giving you full control over exactly which assets get migrated.
Migration options include:
- Selecting specific assets for migration
- Choosing whether tasks should start automatically or remain paused by default
- Upgrading existing Talend 7 artifacts to Talend 8 using the included sandbox environment
Prerequisites and how to get started
- For all requirements, setup instructions, and details, see Region Mover | Qlik Talend Cloud Migration Toolkit Documentation
- Qlik Talend Cloud Migration Toolkit R2026-08 or later is required
Download
Download the latest release from the Migration Center page on Qlik Help.
Thank you for choosing Qlik,
Qlik Support -
Qlik Digest - Data Edition - September 2026
The real blocker behind stalled agentic AI rollouts isn't the models, you can now build a governed data product without hand-coding a single pipeline, and AriensCo shows how cutting 83% of its data platforms got its developers back on real work. -
Qlik Digest - Analytics Edition - September 2026
The real blocker behind stalled agentic AI rollouts isn't the models, early access to what's coming next in Qlik is open now, and Valpak shows how plain-language reporting turned compliance into something customers trust and pay for. -
Declarative Pipelines in Qlik Talend Cloud
Get a quick look at Declarative Pipelines in Qlik Talend Cloud in just 4 minutes. -
Qlik がエージェンティックデータエンジニアリングの一般提供を開始（Qlik Blog 翻訳）
ブログ著者：Matt Hayes本ブログは「Qlik Agentic Data Engineering is Generally Available. Here's What That Actually Means.」の翻訳になります。 4月に米国で開催された「Qlik Connect」の際、チームがパイプライン構築を超えて、自律的な AI エージェントを活用できる、信頼できるデータ基盤の設計へと向かっているという変化について、ブログを投稿しました。 そして現在、Qlik は、データチームがこの変化を認識する段階から、実際に運用する段階へと進むための支援を行っています。エージェンティックデータエンジニアリングの各機能が、Qlik Talend Cloud® において一般提供されました。 エージェンティックデータエンジニアリングは、2026年を象徴する話題の 1 つです。Gartner 社が 2026年 2月に発表した「Top Trends in Data & Analytics」レポー... Show Moreブログ著者：Matt Hayes
本ブログは「Qlik Agentic Data Engineering is Generally Available. Here's What That Actually Means.」の翻訳になります。4月に米国で開催された「Qlik Connect」の際、チームがパイプライン構築を超えて、自律的な AI エージェントを活用できる、信頼できるデータ基盤の設計へと向かっているという変化について、ブログを投稿しました。
そして現在、Qlik は、データチームがこの変化を認識する段階から、実際に運用する段階へと進むための支援を行っています。エージェンティックデータエンジニアリングの各機能が、Qlik Talend Cloud® において一般提供されました。
エージェンティックデータエンジニアリングは、2026年を象徴する話題の 1 つです。Gartner 社が 2026年 2月に発表した「Top Trends in Data & Analytics」レポートでは、2029年までに、適応性があり状況を認識する AI エージェントによるエージェンティックデータマネジメントが、データエンジニアリングのワークフローの 75% を自動化し、より価値の高い業務にリソースを解放すると予測されています。
この予測こそ、Qlik と今回のリリースが実現するものです。そして、私たちがデータを AI のために機能させているというもう一つの証明でもあります。
無料トライアルを試す一般提供を開始した製品
データエージェント
Qlik は、2026年 2月にエージェンティックエクスペリエンスを発表しました。今回のリリースでは、データエンジニアリングのワークフローに特化して構築された新しいエージェントによって、このエクスペリエンスをデータエンジニアリングの領域へと拡張します。- Data Product Agent - 高品質にキュレーションされたデータプロダクトの仕様定義 / 作成 / ガバナンス / 可視化を担います。
- Data Quality Agent - データの正確性 / 完全性 / 信頼性を維持し、データスチュワードによるデータセット内のプロファイリング / モニタリング / エラー修復を積極的に支援します。
- Catalog and Business Glossary Agent - データ資産の発見 / 分類 / ドキュメント化を自動化します。さらに、組織全体におけるビジネス用語の定義 / ガバナンス / 標準化も担います。これにより、人間 / アプリ / エージェントのすべてが同じ意味論的な基盤の上に立てるようにします。
- Pipeline Agent - 多様な環境を横断したインテリジェントなデータパイプラインの構築と展開を自動化します。今四半期の後半にプレビュー公開され、今年後半に一般提供を予定しています。
こうしたエージェントは、既存のワークフローの上に重ねられた単なる AI アシスタントではありません。自らの動作環境を理解し、関連するビジネス状況を処理した上で行動する自律した目標思考型のコンポーネントです。これこそが、「作業を助けるツール」と「共に働くシステム」との、アーキテクチャ上の決定的な違いです。
宣言型データパイプライン
お好みの統合開発環境上で、自然言語で Qlik のデータパイプラインを構築・更新することも可能になりました。現時点では、最も広く使われている組み合わせである、Claude Code または GitHub Copilot と VS Code の併用を推奨していますが、今後、対応する統合開発環境をさらに拡大していく予定です。
これからは、エンジニアが「意図」を記述するだけで完了できます。実装はコーディングエージェントが行います。本番投入前に手直しが必要な試作品ではなく、初日からガバナンスの効いた品質スコアが付与されたパイプラインを生成してくれます。
エージェンティックルーティングの強化
今回のリリースには、エンタープライズ向けのエージェンティックシナリオに対応する大幅に拡張されたコンテキスト・メモリウィンドウも追加されました。複雑な多段階のワークフローを構築するチームから最も多く寄せられていた要望に応えるべく実現しました。データの分類、セマンティックエンリッチメント、RAG パイプライン、そして動的ルーティングが、エンタープライズ規模の導入に求められるレベルで、事象主導型の統合フロー内で利用可能になりました。
なぜこれが重要なのか？あなたの役割にどう影響するのか？上記の機能は、技術的な側面の回答です。より重要なのは、こうした機能がデータ基盤を運用する人や、それに依存するビジネスにとって、実際に何を意味するのかという点です。
データエンジニアまたはデータアーキテクトの方は…
現在、業務時間の大半を占めている、プロファイリング・カタログ整備・品質改良・パイプラインの展開や保守といった作業こそが、これらのエージェントが担うために設計された仕事です。エージェントは、あなたの役割を奪う脅威ではありません。エージェンティック時代が求めるレベルで業務を実行するために、生産性を飛躍的に高めてくれる力になります。今後数年間で最も価値を発揮するエンジニアとは、新しいツールを活用できる人、そしてエージェンティックシステムが信頼し、その中で推論できるようなデータエコシステムを設計できる人です。彼らはコンテキストレイヤーを提供します。ガバナンスのガードレールを実装します。そして、あるフィールドを読み取った際に、生の値だけでなく、ビジネス上何を意味するのかを理解できるセマンティックな基盤を提供します。
さらに、宣言型データパイプラインで生産性を高めているコーディングエージェントを利用しながら、最初の確約段階から本番環境に耐えうる品質を保証することができます。あなたの業務内容が変わるわけではありません。働き方の効果を何倍にも高めるインフラを利用できるのです。
Head of Data / CIO / CDO の方は…
企業における AI への投資は、AI に提供されるデータの質に左右されます。目新しい指摘ではありませんが、エージェンティック時代においては、バッチ処理の時代のデータ問題とは比較にならないほど影響が即座に現れます。
人間のアナリストが不完全なデータを扱う場合、人間の判断力が働きます。なにかがおかしいと気づくことができますが、AI エージェントは気づくことができません。与えられたデータの品質を問わず、機械的に高速処理をします。「使用可能に見えるデータ」と「実際に使用可能なデータ」との間にあるギャップこそが、誰にも原因を特定されることなく AI の ROI が静かに失われていく原因です。
データ基盤が整えば、3 つの成果が変わります。- 貴社の AI システムは、確信を持って判断の根拠を示せる結果を導き出します。ガバナンスの効いた品質スコアが適用され、完全なデータの来歴が確保されたデータソースまで追跡することが可能になります。
- AI の判断が正しいかどうかを検証する作業から解放されるため、AI が提示した内容に基づいた具体的なアクションに注力できるようになります。
- 手動によるパイプライン保守や事後対応の品質改良から解放されるため、エンジニアリングのリソースをビジネスの差別化につながる新たな能力の開発に配分できるようになります。
データに依存する業務を行う事業部門の方は…
オペレーション・財務・サプライチェーン・顧客対応といったチームが利用する AI システムは、利用するデータがビジネス状況に適しており、最新で品質スコアが付与されているほど、より的確な意思決定ができるようになります。現在、数値の正確性を疑ったり、異なるシステムから出てくる矛盾した結果を照合したり、データパイプラインの修正をデータエンジニアリングチームに依頼して待機することに費やしている時間こそが、今回のリリースで削減を期待できる「コスト」なのです。
今日から、ぜひ始めて欲しいこと
- エージェンティックデータエンジニアリングの各機能は、現在 Qlik Talend Cloud でご利用いただけます。
- Qlik Talend Cloud をまだ導入されていない場合は、無料トライアルをお試しください。あらゆる環境間で信頼できるデータの移行と変換をご体験いただけます。
パイプラインの時代が終わったのは、パイプラインが機能しなくなったからではありません。基盤が使う側の変化に追いつけなかったからです。
今回のリリースの決定的な違いは、Qlik Talend Cloud を利用していても、データが実際に存在するあらゆる環境で運用していても、後からデータ品質とガバナンスを追加するのではなく、最初から統合された形で提供しているという点です。
これが、「一般提供」という言葉が意味するところです。 - Data Product Agent - 高品質にキュレーションされたデータプロダクトの仕様定義 / 作成 / ガバナンス / 可視化を担います。
-
Qlik Cloud Analytics: "When data source is updated" event has returned
When we introduced enhanced self-service scheduling in April 2025, we removed the When data is refreshed option, which had let reload schedules trigger automatically when a dependent dataset was updated. At the time, we weren't able to carry that capability forward into the new task-based scheduler right away. That capability is now returning. See What's New in Qlik Cloud and Scheduling data refreshes with tasks. In the task editor, under Based o... Show MoreWhen we introduced enhanced self-service scheduling in April 2025, we removed the When data is refreshed option, which had let reload schedules trigger automatically when a dependent dataset was updated. At the time, we weren't able to carry that capability forward into the new task-based scheduler right away.
That capability is now returning. See What's New in Qlik Cloud and Scheduling data refreshes with tasks.
In the task editor, under Based on > Event, you can now select When data is refreshed to trigger a task automatically when a data update is detected in an upstream Qlik Talend Data Integration project that loads data into an analytics application.
The option is only available if the application is connected to a Qlik Talend Data Integration pipeline.
This brings back the event-driven automation the old scheduler offered, now built natively into the new self-service scheduling framework, with full compatibility with the multi-task model.
What does this mean for me?
If the application has an existing When data is refreshed schedule, this button might instead say Migrate. For applications with these schedules, clicking Migrate or Save will migrate all associated schedules to be individual tasks attached to the application.
No other action is required.
We're happy to assist with any follow-up questions. Reply to this blog post or take your queries to our Support Chat.
Thank you for choosing Qlik,
Qlik Support -
Introducing feature previews!
For years, new Qlik Cloud capabilities have arrived the same way: finished. That sounds good until you notice what it means. We only hear what the broader user base thinks once something is generally available, which is the exact moment when changing it is most expensive. -
From Analytics to AI: Building Skills for the Future
The skills students need for the workplace are changing quickly. Analytics is still a core part of that, but it is no longer the whole picture. Today, students are also being introduced to AI, predictive analytics, machine learning, and new ways of interacting with data. For educators, that means thinking not only about what students need to learn now, but also about how to prepare them for technologies that will continue to evolve. -
Same As It Never Was: Why MCP Is Creating a New Audience for Your Real-Time Data
Talking Heads sang "Once in a Lifetime" in 1980. Its central image - water flowing underground, endlessly, whether anyone's watching or not - was about sleepwalking through your own life while forces beneath the surface keep moving without you. It's also, unintentionally, a fair description of how enterprise data behaves: constantly flowing beneath the business, mostly unseen, doing its job whether a human ever looks at it or not. What's differen... Show MoreTalking Heads sang "Once in a Lifetime" in 1980. Its central image - water flowing underground, endlessly, whether anyone's watching or not - was about sleepwalking through your own life while forces beneath the surface keep moving without you. It's also, unintentionally, a fair description of how enterprise data behaves: constantly flowing beneath the business, mostly unseen, doing its job whether a human ever looks at it or not. What's different isn't the flow. It's who's drinking from it. Qlik, SAP, and a cluster of vendors at API World have all recently opened the tap to a new consumer - AI agents -via a shared standard called MCP (Model Context Protocol). Same water. Different drinker.
-
Introducing Qlik Cloud Public Feature Previews for everyone
Our recently launched Public Previews give you early, hands-on access to what's coming next in Qlik Cloud, before the previewed features are generally available. Try new capabilities, shape their direction with your feedback, and stay ahead of the latest features. Public Previews are enabled by default for most users and are directly accessible from your profile: A tenant admin needs to activate the feature preview program. Read all about it in ... Show MoreOur recently launched Public Previews give you early, hands-on access to what's coming next in Qlik Cloud, before the previewed features are generally available. Try new capabilities, shape their direction with your feedback, and stay ahead of the latest features.
Public Previews are enabled by default for most users and are directly accessible from your profile:
A tenant admin needs to activate the feature preview program.
Read all about it in Introducing feature previews (Innovation Blog).
The Highlights
- Shape the roadmap: Share your feedback directly in the product and inform how Qlik Cloud evolves.
- Stay up to date: Join Public Previews on Qlik Community, where our product team will advertise the available preview features.
- You control your experience: Turn your personal preview experience on or off at any time - and as a tenant admin, manage who has access to the previews through a custom role.
Ready to know more?
Getting started is quick and easy. Here is all you need:
- Public Previews | Qlik Community
-
Introducing feature previews
- Managing feature preview for your tenant
- What's New | Qlik Help
Thank you for choosing Qlik,
Qlik Support -
Action required: Qlik Automate ServiceNow connector migration to OAuth 2.0, June...
Qlik Automate's ServiceNow connector is moving from username and password authentication to OAuth 2.0. This change aligns with security best practices and ServiceNow's own recommendations for third-party integrations, eliminating the need to store credentials in plain text and providing more granular, revocable access control. When will this change be made? The change will go into effect on the 23rd of June, 2026. What action do I need to tak... Show MoreQlik Automate's ServiceNow connector is moving from username and password authentication to OAuth 2.0. This change aligns with security best practices and ServiceNow's own recommendations for third-party integrations, eliminating the need to store credentials in plain text and providing more granular, revocable access control.
When will this change be made?
The change will go into effect on the 23rd of June, 2026.
What action do I need to take?
Existing connections that use username and password authentication will need to be re-authenticated using OAuth 2.0. Complete the re-authentication steps as outlined in this blog post on the 23rd of June to prevent possible service interruptions.
How do I switch my ServiceNow connection to OAuth 2.0?
ServiceNow provides guidance on each stage of the OAuth 2.0 setup. See the following for details:
- OAuth 2.0 Overview
- Set up OAuth
- OAuth Inbound
- OAuth Inbound and Outbound authentication
- Enable OAuth with inbound REST
To migrate your Qlik Automate connector, first prepare ServiceNow by configuring OAuth 2.0, then re-authenticate Qlik Automate on the 23rd of June.
Before you begin, make sure you have Admin access to your ServiceNow instance and Admin or Owner access to your Qlik Cloud tenant and the relevant Qlik Automate automation.
- Open the Application Manager in ServiceNow:
The OAuth 2.0 plugin must be available in your ServiceNow instance.
- Log in to your ServiceNow instance.
- Click the All button in the top-left navigation bar and search for Application Manager.
- Select Application Manager from the results under Admin Center.
- In the Application Manager, use the Search your licensed applications and plugins field to search for OAuth. The ServiceNow products OAuth tile will appear in the results.
- Click the OAuth tile to expand it, then install the OAuth 2.0 plugin (Plugin ID: com.snc.platform.security.oauth). Wait for the installation to complete before proceeding.
- Navigate to Inbound Integrations:
- Click the All button again and search for Inbound Integrations.
- Select it from under System OAuth in the results.
- Create a new OAuth application endpoint:
- Click the New Integration button on the right.
- On the connection type screen, select OAuth – Authorization code grant.
- Configure the application by providing a Name, the Redirect URL, and the required scopes.
When prompted for a Redirect URL, use the callback URL provided by Qlik Automate during the connection setup. This URL must exactly match what is registered in ServiceNow.
- Save the Client ID and Client Secret; they are required for the next step.
- Click Save.
- Re-authenticate the connector in Qlik Automate
This step can only be carried out after the change on the 23rd of June, 2026.
- In Qlik Automate, add a new ServiceNow connection.
- Enter your ServiceNow instance domain (format: https://[domain].service-now.com/).
- Provide the Client ID and Client Secret previously recorded.
- Follow the on-screen authentication flow to complete the OAuth authorisation.
If you encounter issues during the migration, please contact Qlik Support or visit the Qlik Community for assistance. When raising a support case, include your ServiceNow instance domain and the error message you are seeing.
Thank you for choosing Qlik,
Qlik Support -
Qlik Datathon 2026: Empowering Future Leaders to "Think Like a Manager"
On 13 August 2026, Kristu Jayanti University successfully hosted the third edition of the Qlik Datathon 2026, themed "Think Like a Manager." This flagship analytics competition brought together aspiring data professionals, encouraging them to apply analytics, artificial intelligence, and business thinking to solve real-world challenges. This year's event marked a significant milestone as the first-ever inter-university Qlik Datathon, creating a l... Show MoreOn 13 August 2026, Kristu Jayanti University successfully hosted the third edition of the Qlik Datathon 2026, themed "Think Like a Manager." This flagship analytics competition brought together aspiring data professionals, encouraging them to apply analytics, artificial intelligence, and business thinking to solve real-world challenges.
This year's event marked a significant milestone as the first-ever inter-university Qlik Datathon, creating a larger platform for collaboration, innovation, and healthy competition among students from leading institutions.
-
Qlik MCP Just Got Smarter About Data Pipelines with Three New Lookup Tools for A...
Ask your coding agent a real question about your Qlik tenant and get a factual answer in real time. Qlik's MCP server now ships three new lookup tools purpose-built for declarative pipeline development, so Claude Code, Copilot, and Codex can check spaces, connections, and table structures against your live environment instead of guessing. No more tabbing out to the Qlik Cloud web app to hunt down a connection name or table ID, just faster, more a... Show MoreAsk your coding agent a real question about your Qlik tenant and get a factual answer in real time. Qlik's MCP server now ships three new lookup tools purpose-built for declarative pipeline development, so Claude Code, Copilot, and Codex can check spaces, connections, and table structures against your live environment instead of guessing. No more tabbing out to the Qlik Cloud web app to hunt down a connection name or table ID, just faster, more accurate pipelines from the first prompt.
-
Watch! Q&A with Qlik: App Development
Don't miss our previous Q&A with Qlik! Pull up a chair and chat with our panel of experts to help you get the most out of your Qlik experience. Let our Qlik experts offer creative solutions to your analytics demands and answer your visualization questions. WATCH HERE
-
Qlik Talend® Unlocked: See How Leading Teams Modernize Talend
Qlik Talend Unlocked is a monthly series where engineers who have shipped this into production show you how. Each session takes on a real part of the modern Talend lifecycle, from CI/CD job promotion and test automation to migration, open lakehouse architectures, and real time integration. Practical approaches you can take straight back to your own environment, with results teams can measure.Episode one is on demand now, episode two is open for r... Show MoreQlik Talend Unlocked is a monthly series where engineers who have shipped this into production show you how. Each session takes on a real part of the modern Talend lifecycle, from CI/CD job promotion and test automation to migration, open lakehouse architectures, and real time integration. Practical approaches you can take straight back to your own environment, with results teams can measure.
Episode one is on demand now, episode two is open for registration. Register once and you are set for the whole series.
-
The Final Whistle: Who Takes the Trophy - Model or Mastery?
The World Cup is over, Spain are champions, and the third and final episode of our Model vs. Mastery podcast series has wrapped up with a verdict on the question we've been asking all along: when it comes to predicting football's biggest tournament, does the edge belong to the model or the human expert? Host Adam sat down with Steve Palmer and Nick Magnuson to close out the series, and the results were more decisive than anyone on the losing end... Show MoreThe World Cup is over, Spain are champions, and the third and final episode of our Model vs. Mastery podcast series has wrapped up with a verdict on the question we've been asking all along: when it comes to predicting football's biggest tournament, does the edge belong to the model or the human expert?
Host Adam sat down with Steve Palmer and Nick Magnuson to close out the series, and the results were more decisive than anyone on the losing end expected.
-
“Where is Qlik headed with AI?”
So when people ask, “Where is Qlik headed with AI?” I think there’s a better question:
