Amazon Quick Sight is a fully managed, cloud-native business intelligence (BI) capability for building and publishing interactive dashboards. The new hierarchy filter gives dashboard authors rich, multi-level filtering in a single compact control, reducing clutter and guiding readers to the data they need in fewer steps.

Amazon Quick introduces Quick Essentials for enterprises. The plan makes it easier for organizations to get started with all the features of Quick such as AI-powered chat, Research, Flows, and Apps, and lets users view and interact with Quick Sight dashboards and reports and then manage adoption at the desired pace. In AWS Regions where Amazon Quick is available, Quick Sight Reader users are upgraded to Quick Essentials at no additional per-user cost. With Quick Essentials, Quick Sight Readers can ask their dashboards questions in plain language, like what drove a revenue dip in March, and dig into the details with follow-up questions. They can turn the answer into a document, presentation, or spreadsheet for their team. When they need more context, Research pulls from their data, files, and the web into a detailed report with citations. If they need the same update every week, Flows can build it and send it automatically. When they need a tool that doesn't exist yet, like a request tracker, they can describe it and Apps builds it, without writing code. Existing dashboards, Favorites, and Recents stay in place. Row-level and column-level security apply to every answer, and data is not shared across customers or used to train shared models. Administrators continue to manage the capabilities with custom permission profiles that can be applied to any user or a role. Quick Essentials is enabled in a phased rollout across AWS Regions where Quick AI features are available. To learn more, read the Amazon Quick Community blog post. For pricing details, visit the Amazon Quick pricing page.

Amazon Quick introduces Quick Essentials for enterprises. The plan makes it easier for organizations to get started with all the features of Quick such as AI-powered chat, Research, Flows, and Apps, and lets users view and interact with Quick Sight dashboards and reports and then manage adoption at the desired pace. In AWS Regions where Amazon Quick is available, Quick Sight Reader users are upgraded to Quick Essentials at no additional per-user cost. With Quick Essentials, Quick Sight Readers can ask their dashboards questions in plain language, like what drove a revenue dip in March, and dig into the details with follow-up questions. They can turn the answer into a document, presentation, or spreadsheet for their team. When they need more context, Research pulls from their data, files, and the web into a detailed report with citations. If they need the same update every week, Flows can build it and send it automatically. When they need a tool that doesn't exist yet, like a request tracker, they can describe it and Apps builds it, without writing code. Existing dashboards, Favorites, and Recents stay in place. Row-level and column-level security apply to every answer, and data is not shared across customers or used to train shared models. Administrators continue to manage the capabilities with https://docs.aws.amazon.com/quick/latest/userguide/custom-permissions.html profiles that can be applied to any user or a role. Quick Essentials is enabled in a phased rollout across https://docs.aws.amazon.com/quick/latest/userguide/regions.html#regions-qs. To learn more, read the https://community.amazonquick.com/t/every-reader-gets-professional-capabilities/53958. For pricing details, visit the https://aws.amazon.com/quick/pricing/.

Learn how to embed individual Amazon Quick Sight visuals into a React application with per-user access control. This walkthrough uses Amazon Cognito authentication and a serverless AWS Lambda backend to generate scoped embed URLs, deployed with a single AWS CloudFormation stack.

AWS announces the availability of TwelveLabs Marengo 3.0 as an embedding model in Amazon Bedrock Managed Knowledge Base, enabling customers to create multimodal embeddings for video, audio, and image content. Amazon Bedrock Managed Knowledge Base already supports media search by transcribing audio and video to text and generating text-based embeddings—Marengo 3.0 goes further by encoding visual scenes, speech, and video cues directly into multimodal embeddings, capturing meaning that transcription alone cannot. Simply upload your media assets from data sources such as Amazon S3, sync, and search using natural language—with no infrastructure to manage. Marengo 3.0 produces compact 512-dimensional vectors, delivering state-of-the-art retrieval accuracy. Results include segment start and end times, enabling applications to jump directly to the relevant moment in a video. This unlocks use cases across sports analytics, media and entertainment, security, education, and retail—from finding specific plays across seasons of game footage to locating lecture segments by concept rather than keywords. The model offers configurable segmentation options to match your content structure. To learn more, see TwelveLabs Marengo 3.0 embedding model integration in the Amazon Bedrock Knowledge Base User Guide. For more information, visit the Amazon Bedrock Knowledge Bases product page.

AWS announces the availability of TwelveLabs Marengo 3.0 as an embedding model in Amazon Bedrock Managed Knowledge Base, enabling customers to create multimodal embeddings for video, audio, and image content. Amazon Bedrock Managed Knowledge Base already supports media search by transcribing audio and video to text and generating text-based embeddings—Marengo 3.0 goes further by encoding visual scenes, speech, and video cues directly into multimodal embeddings, capturing meaning that transcription alone cannot. Simply upload your media assets from data sources such as Amazon S3, sync, and search using natural language—with no infrastructure to manage. Marengo 3.0 produces compact 512-dimensional vectors, delivering state-of-the-art retrieval accuracy. Results include segment start and end times, enabling applications to jump directly to the relevant moment in a video. This unlocks use cases across sports analytics, media and entertainment, security, education, and retail—from finding specific plays across seasons of game footage to locating lecture segments by concept rather than keywords. The model offers configurable segmentation options to match your content structure. To learn more, see https://docs.aws.amazon.com/bedrock/latest/userguide/kb-managed-native-multimodal.html in the Amazon Bedrock Knowledge Base User Guide. For more information, visit the https://aws.amazon.com/bedrock/knowledge-bases/.

The Amazon Quick desktop app is now generally available on macOS and Windows. The desktop app brings the full power of Amazon Quick to your computer, working directly with your local files and staying connected to your calendar, email, and business apps in the background. Quick keeps your conversations, context, and agents synchronized across the desktop and mobile applications, so work you start on one surface carries over to the other, enabling you to work wherever you want.  Additionally, with this release, Amazon Quick agents run continuously in the background, even after you close your computer, so long-running work keeps making progress while you're away. Start an agent before you leave the office, provide additional inputs from the mobile app during your commute home, and then review the final output when you arrive. Quick offers production-grade stability, maintains AWS SLA commitments, and offers the governance and administrative controls for deployments at enterprise scale.  The Amazon Quick desktop app is available in 7 regions, US East (N. Virginia), Asia Pacific (Sydney), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Tokyo), and Europe (Frankfurt)  Existing Quick users can download the desktop app from here. The Quick mobile application is available for free from the Apple App Store and Google Play Store.

Today, Amazon Quick offers new capabilities that make it easier to organize your work, govern it across an organization, and trust the answers it produces. These capabilities build on Amazon Quick across desktop and mobile, bringing enterprise-grade management, richer collaboration, and always-on intelligence to teams wherever they work.  Your agents no longer stop when you step away. Scheduled tasks and monitoring agents run in the cloud and deliver results to your feed even when your laptop is closed. A sharper activity feed adds top-level filters, an improved catch-up view, a daily briefing that refreshes three times a day, and search across up to seven days of feed data, so you see what needs you first. Administrators gain mobile device management support, custom per-user permissions, and Microsoft Purview data loss prevention integration. Teams can share files and publish agents and skills for others to discover and install, and browse a catalog of official skills. Quick spaces and Quick apps now run natively on the desktop, any indexed local folder can become a searchable space, and inline citations let you verify every answer against its source. Additionally, every Quick subscriber now gets more agent hours each month — Professional grows from 4 to 8 and Enterprise from 8 to 18 — combined into a single, simpler allotment.  New users can create an account for free and start using Quick in minutes.Or to learn more,  visit the Amazon Quick product page.

The Amazon Quick activity feed is now available on the Amazon Quick mobile app for iOS and Android, keeping you connected to your most important work from anywhere.  The activity feed is your single, prioritized view of everything that needs your attention across your enterprise communications and tools, so you don't have to check each one separately. Items requiring your attention populate the top of your feed, and instead of switching between apps, you can take action directly from within Quick.  Never miss something time-sensitive, even when you're away from your desk. Your decide which notifications are important and which are noise. Over time, Quick learns your priorities and surfaces only the things that matter.  You can also ask Quick to post anything to your feed through a routine, pulling from any connected data source. For example, you can tell Quick “every morning at 7:30, tell me which customer meetings I have that day and give me 3 bullet points to prep”.   Additionally, as part of today's announcement, Amazon Quick retains context across the desktop and mobile applications. Any work you do on one surface carries over to the other, so you can start a chat or assign a task to an agent on your desktop, then review progress and continue the chat from your mobile device, picking up right where you left off when you're back at your computer.  The Amazon Quick mobile app is included with your existing Amazon Quick access at no additional cost.  Existing Quick customers can download the Quick mobile application for iOS from the Apple App Store, and Android from the Google Play Store. If you're new to Quick, visit the Quick Product Page to create an account for free in minutes.

Today, Amazon Quick offers new capabilities that make it easier to organize your work, govern it across an organization, and trust the answers it produces. These capabilities build on Amazon Quick across desktop and mobile, bringing enterprise-grade management, richer collaboration, and always-on intelligence to teams wherever they work.  Your agents no longer stop when you step away. Scheduled tasks and monitoring agents run in the cloud and deliver results to your feed even when your laptop is closed. A sharper activity feed adds top-level filters, an improved catch-up view, a daily briefing that refreshes three times a day, and search across up to seven days of feed data, so you see what needs you first. Administrators gain mobile device management support, custom per-user permissions, and Microsoft Purview data loss prevention integration. Teams can share files and publish agents and skills for others to discover and install, and browse a catalog of official skills. Quick spaces and Quick apps now run natively on the desktop, any indexed local folder can become a searchable space, and inline citations let you verify every answer against its source. Additionally, every Quick subscriber now gets more agent hours each month — Professional grows from 4 to 8 and Enterprise from 8 to 18 — combined into a single, simpler allotment.  New users can https://aws.amazon.com/quick/download/ and start using Quick in minutes.Or to learn more,  visit the https://aws.com/quick

The Amazon Quick desktop app is now generally available on macOS and Windows. The desktop app brings the full power of Amazon Quick to your computer, working directly with your local files and staying connected to your calendar, email, and business apps in the background. Quick keeps your conversations, context, and agents synchronized across the desktop and mobile applications, so work you start on one surface carries over to the other, enabling you to work wherever you want.  Additionally, with this release, Amazon Quick agents run continuously in the background, even after you close your computer, so long-running work keeps making progress while you're away. Start an agent before you leave the office, provide additional inputs from the mobile app during your commute home, and then review the final output when you arrive. Quick offers production-grade stability, maintains AWS SLA commitments, and offers the governance and administrative controls for deployments at enterprise scale.  The Amazon Quick desktop app is available in 7 regions, US East (N. Virginia), Asia Pacific (Sydney), US West (Oregon), Europe (Ireland), Europe (London), Asia Pacific (Tokyo), and Europe (Frankfurt)  Existing Quick users can download the desktop app from https://aws.amazon.com/quick/download/. The Quick mobile application is available for free from the https://apps.apple.com/us/app/amazon-quick/id1148226615 and https://play.google.com/store/apps/details?id=com.amazonaws.quicksight.mobile&hl=en_US.

The Amazon Quick activity feed is now available on the Amazon Quick mobile app for iOS and Android, keeping you connected to your most important work from anywhere.  The activity feed is your single, prioritized view of everything that needs your attention across your enterprise communications and tools, so you don't have to check each one separately. Items requiring your attention populate the top of your feed, and instead of switching between apps, you can take action directly from within Quick.  Never miss something time-sensitive, even when you're away from your desk. Your decide which notifications are important and which are noise. Over time, Quick learns your priorities and surfaces only the things that matter.  You can also ask Quick to post anything to your feed through a routine, pulling from any connected data source. For example, you can tell Quick “every morning at 7:30, tell me which customer meetings I have that day and give me 3 bullet points to prep”.   Additionally, as part of today's announcement, Amazon Quick retains context across the desktop and mobile applications. Any work you do on one surface carries over to the other, so you can start a chat or assign a task to an agent on your desktop, then review progress and continue the chat from your mobile device, picking up right where you left off when you're back at your computer.  The Amazon Quick mobile app is included with your existing Amazon Quick access at no additional cost.  Existing Quick customers can download the Quick mobile application for iOS from the https://apps.apple.com/us/app/amazon-quick/id1148226615 and Android from the https://play.google.com/store/apps/details?id=com.amazonaws.quicksight.mobile&hl=en_US. If you're new to Quick, visit the https://aws.com/quick to create an account for free in minutes. 

AWS announces the Confluence Data Center data source connector for Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service. Customers running self-hosted Confluence Data Center instances can now crawl blogs and pages from their Confluence spaces directly into their managed knowledge base. Previously, bringing Confluence Data Center content into Bedrock Knowledge Bases required building custom ingestion pipelines—now, you provide your instance credentials, and the connector handles data crawling, metadata extraction, and incremental sync automatically. The Confluence Data Center connector gives your AI agents access to the institutional knowledge your teams already maintain in Confluence, including wiki pages and blog posts across spaces. You can use filters to scope crawls to specific spaces or content types, ensuring only relevant content is ingested and keeping your knowledge base focused and cost-efficient. This makes it easy to power internal assistants grounded in engineering documentation, runbooks, or team knowledge bases hosted on Confluence Data Center. To learn more, see Confluence Data Center data source connector in the Amazon Bedrock User Guide. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.

AWS announces the Confluence Data Center data source connector for Amazon Bedrock Managed Knowledge Base, a fully managed retrieval-augmented generation (RAG) service. Customers running self-hosted Confluence Data Center instances can now crawl blogs and pages from their Confluence spaces directly into their managed knowledge base. Previously, bringing Confluence Data Center content into Bedrock Knowledge Bases required building custom ingestion pipelines—now, you provide your instance credentials, and the connector handles data crawling, metadata extraction, and incremental sync automatically. The Confluence Data Center connector gives your AI agents access to the institutional knowledge your teams already maintain in Confluence, including wiki pages and blog posts across spaces. You can use filters to scope crawls to specific spaces or content types, ensuring only relevant content is ingested and keeping your knowledge base focused and cost-efficient. This makes it easy to power internal assistants grounded in engineering documentation, runbooks, or team knowledge bases hosted on Confluence Data Center. To learn more, see Confluence Data Center data source connector in the https://docs.aws.amazon.com/bedrock/latest/userguide/kb-managed-ds-confluence-onprem.html. For more information about Amazon Bedrock Managed Knowledge Base, visit the https://aws.amazon.com/bedrock/knowledge-bases/.

AWS announces the CheckIngestedDocumentAcl and GetIngestedDocumentAcl APIs for Amazon Bedrock Managed Knowledge Base, giving customers a self-service way to debug document access issues and audit document-level permissions. When a user doesn't see an expected document in retrieval results for ACL-enabled data sources, it can be difficult to determine whether the cause is an access control misconfiguration or something else entirely. These new APIs and the accompanying console experience close that gap, enabling you to quickly diagnose and resolve permission issues without opening a support case. CheckIngestedDocumentAcl lets you verify whether a specific user has access to a given ingested document, while GetIngestedDocumentAcl returns the full ACL attached to a document so you can audit exactly what permissions are configured and catch misconfigurations. The console also introduces a new Document Access Control section on the data source details page, where you can check access by entering a document ID and user email or retrieve a document's full ACL by document ID. Together, these capabilities give administrators the visibility they need to manage access control at scale across enterprise knowledge bases. To learn more, see CheckIngestedDocumentAcl and GetIngestedDocumentAcl in the Amazon Bedrock API Reference. For more information about Amazon Bedrock Managed Knowledge Base, visit the Amazon Bedrock Knowledge Bases product page.

AWS announces the CheckIngestedDocumentAcl and GetIngestedDocumentAcl APIs for Amazon Bedrock Managed Knowledge Base, giving customers a self-service way to debug document access issues and audit document-level permissions. When a user doesn't see an expected document in retrieval results for ACL-enabled data sources, it can be difficult to determine whether the cause is an access control misconfiguration or something else entirely. These new APIs and the accompanying console experience close that gap, enabling you to quickly diagnose and resolve permission issues without opening a support case. CheckIngestedDocumentAcl lets you verify whether a specific user has access to a given ingested document, while GetIngestedDocumentAcl returns the full ACL attached to a document so you can audit exactly what permissions are configured and catch misconfigurations. The console also introduces a new Document Access Control section on the data source details page, where you can check access by entering a document ID and user email or retrieve a document's full ACL by document ID. Together, these capabilities give administrators the visibility they need to manage access control at scale across enterprise knowledge bases. To learn more, see https://docs.aws.amazon.com/bedrock/latest/APIReference/API_agent-runtime_CheckIngestedDocumentAcl.html and https://docs.aws.amazon.com/bedrock/latest/APIReference/API_agent-runtime_GetIngestedDocumentAcl.html in the Amazon Bedrock API Reference. For more information about Amazon Bedrock Managed Knowledge Base, visit the https://aws.amazon.com/bedrock/knowledge-bases/.

Amazon Quick announces support for no data message customization, enabling authors to replace the default "No data to display" message with a tailored message when a visual returns no data. Authors can configure a custom title, subtitle, and hyperlink that give readers immediate context about why no data is shown and what steps to take next. All text fields support parameters, so the message can dynamically reflect the reader's current filter selections. The hyperlink supports http://, https://, and mailto: URL schemas, and both the title and subtitle can be toggled on or off independently. This feature is available now in all https://docs.aws.amazon.com/quick/latest/userguide/regions.html. To learn more, visit https://docs.aws.amazon.com/quick/latest/userguide/analysis-settings.html in the Amazon Quick User Guide.

Amazon Quick announces support for no data message customization, enabling authors to replace the default "No data to display" message with a tailored message when a visual returns no data. Authors can configure a custom title, subtitle, and hyperlink that give readers immediate context about why no data is shown and what steps to take next. All text fields support parameters, so the message can dynamically reflect the reader's current filter selections. The hyperlink supports http://, https://, and mailto: URL schemas, and both the title and subtitle can be toggled on or off independently. This feature is available now in all AWS Regions where Amazon Quick is offered. To learn more, visit Analysis Settings in the Amazon Quick User Guide.

AWS Transform customers can now use BI migration agents to convert Tableau and Power BI dashboards to Amazon Quick Sight (BI capability of Amazon Quick) assets, helping reduce migration effort from months to days. These agents are built by https://wavicledata.com/bi-migration-aws-transform/?utm_campaign=42551559-2026%20Q2%20AWS%20Transform&utm_source=AWS%20What%27s%20New%20Post, an AWS Advanced Consulting Partner, leveraging the AWS Transform initiative to create differentiated transformation solutions by integrating specialized agents, tools, knowledge bases, and workflow with AWS Transform’s agentic AI capabilities. Four agents are available for purchase through AWS Marketplace: one Analyzer agent and one Converter agent for each BI migration source (Power BI and Tableau). AWS Transform is a collaborative enterprise IT transformation workbench powered by expert agents, agentic AI systems, and continuous learning that accelerates cloud migration, legacy app modernization, and tech debt reduction. These new BI migration agents are embedded into the AWS Transform workflow and use a chat-based interface to assess your source dashboards for migration readiness, then convert them – rebuilding datasets, calculated fields, visualizations, and filters in Amazon Quick Sight. All processing runs within your AWS account; no data leaves your environment. After conversion, your Amazon Quick administrators assign dashboard ownership to BI authors for validation and publishing. Once migrated, your teams can take advantage of Amazon Quick's AI-powered workflows, including natural-language business questions, automated research, and data-driven actions. The BI migration agents are available through AWS Marketplace in US East (N. Virginia). They support Quick Sight asset creation in all https://docs.aws.amazon.com/general/latest/gr/quicksight.html. To get started, subscribe through AWS Marketplace (https://aws.amazon.com/marketplace/pp/prodview-p7sor3iihijpg?sr=0-5&ref_=beagle&applicationId=AWSMPContessa&utm_campaign=42551559-2026%20Q2%20AWS%20Transform&utm_source=AWS%20Transform%20-%20EZConvertBI%20-%20Power%20BI%20to%20Quick%20Sight&utm_medium=AWS%20Marketplace%20Page or https://aws.amazon.com/marketplace/pp/prodview-dkpskx3mnmk6m?sr=0-4&ref_=beagle&applicationId=AWSMPContessa&utm_campaign=42551559-2026%20Q2%20AWS%20Transform&utm_source=AWS%20Transform%20-%20EZConvertBI%20-%20Tableau%20to%20Quick%20Sight&utm_medium=AWS%20Marketplace%20Page) or contact your AWS account team to explore available programs for free or discounted Amazon Quick migrations. Read more in this https://aws.amazon.com/blogs/machine-learning/aws-transform-now-automates-bi-migration-to-amazon-quick-in-days/.

Amazon Quick now generates dashboards from natural language prompts with Generate Analysis. You describe the dashboard you want, select up to three datasets, and review an editable plan before generation. Amazon Quick then produces organized sheets with visuals selected for your data, filter controls for exploring by different dimensions, and calculated fields such as year-over-year growth and month-over-month comparisons.. Generate Analysis reduces dashboard creation from hours of manual configuration to minutes. With Generate Analysis, you can describe goals such as "create a sales performance dashboard with revenue trends, regional comparisons, and month-over-month growth" and receive a dashboard ready for refinement. The output works with existing publishing workflows, embedding, CI/CD pipelines, and point-and-click editing. At launch, Generate Analysis is available to Enterprise subscription/Author Pro users. Authors also have promotional access to this capability through December 2026 as part of Amazon Quick Enterprise, provided their organization has not restricted access. Generate Analysis is now generally available in all AWS Regions https://docs.aws.amazon.com/quick/latest/userguide/regions.html#regions-qs. To learn more, see https://docs.aws.amazon.com/quick/latest/userguide/generating-an-analysis.html in the Amazon Quick User Guide. To get started, open any dataset in Amazon Quick and choose Generate analysis.

In this post, we walk through how multi-dataset Topics work, explain how the chat agent uses defined relationships to generate cross-dataset queries, and demonstrate an end-to-end implementation using a retail analytics scenario in Quick Sight.

This post is for data architects, business intelligence (BI) engineers, and analytics engineers building or optimizing Quick Sight Topics for natural-language Chat-based exploration.

In this post, we shift from concepts to patterns. For each schema, you’ll find a table structure, use cases, implementation steps, and sample SQL queries. We also cover workarounds for advanced scenarios that require extra modeling steps, and close with a summary of current limitations.

In this post, you will learn how to build an end-to-end integration between Snowflake semantic views and Amazon Quick. The sample data is user review data for a media company. You start by loading movie review data from Amazon Simple Storage Service (Amazon S3) into Snowflake, define a semantic view in SQL to add business meaning, explore it with natural-language queries through Cortex Analyst, and then generate an Amazon Quick dataset and dashboard. The dataset can be created manually or with a provided automation script. By the end, your BI team or AI team can ask natural-language questions against a governed data layer and trust that every response reflects the same business logic.

どーもデータアナリティクス事業本部BIチームのsutoです本日よりAWSDataExportsの一部としてAmazonQuickSightを利用したコストと使用状況のダッシュボードをAWSBil