Building meaningful dashboards requires hours of manual setup, even for experienced BI professionals. Amazon Quick now generates complete multi-page dashboards from natural language input, taking you from one or more datasets to production-ready analytics in minutes. Data analysts creating frequent performance reports, program managers preparing a leadership review, or engineers testing a new dataset can define what they want, and Amazon Quick generates. many sheets are arranged and selected images for your data, filter controls for participants to test on different scales, and calculated fields such as year-on-year growth and month-on-month comparisons. Before production, you review and edit the interactive system of the proposed structure, which keeps you in control of the final result.
In Amazon Quick, Analytics lets you create and edit views, filters, and calculated fields across multiple sheets. When you're ready to share, you publish the analysis as a dashboard. This new AI productivity capability creates analytics and refines them and publishes them as a dashboard with one click.
In this post, we go through generating the analysis in a hurry, we review the plan, and we evaluate the finished result.
What is required
You need the following requirements:
How does this work
To generate an analysis, first select the data you want to analyze. In Amazon Quick, your data is stored in datasets, which connect to sources such as Amazon Redshift, Amazon Simple Storage Service (Amazon S3), or uploaded files. With your dataset ready, you define what you want to see, update the plan, and generate.
Select your dataset
Open the dataset in Amazon Quick and select Generate analysis. You can also start from the Analysis page. Choose 1–3 data sets to analyze. If your data spans multiple tables—orders in one dataset and products in another—you can select them together.
Select Add data adding more data sets if needed.
Define what you want from the analysis/dashboard
Write a natural language prompt describing the information you want to write in the Analysis. Define the business questions, the metrics you care about, and how you want the information organized across the sheets. For example: “Create a performance dashboard that shows order volume trends, revenue KPIs, delivery performance versus estimated delivery days, and product category breakdown by revenue and order count. Include calculated fields for total revenue, average order value, and month-to-month order growth.”
Amazon Quick analyzes your data
Amazon Quick checks your dataset structure and column statistics. You see real-time progress updates as it works: analyzing data set columns, analyzing column statistics, creating an analysis plan.
If you are roaming remotely, use the Analysis → Generations tab to check the status and return to the progress screen.
Review and edit the plan
Amazon Quick presents the Review framework in a two-panel view. I Left pane displays your initial information and a summary of the selected dataset. I right pane shows the proposed layout: sorting controls, sheets, and visuals arranged for each sheet. You can generate quickly or selectively Organize refining the plan first — correcting sheet names, adding or removing visuals, or rearranging the layout.
Generate analysis
Select Produce. Real-time progress updates show each component being built: calculated fields, filters, and each sheet in turn.
Early access writers across operations, engineering, and data science have found this capability to be a significant time saver, turning what used to take hours of manual preparation into minutes of targeted production.
During early access, the author who had never used AI statistics before tested the feature with his first dataset: “The results are amazing and there is no comparison in the time it takes AI to perform analysis and create dashboards versus a human.” – Jeff Sondic, Pre-Construction Manager, GES Ops Construction, Amazon, Ontario Canada
The output is native analysis. It works with existing publishing workflows, embedding patterns, continuous integration and continuous delivery (CI/CD) pipelines, and point-and-click editing in the analytics environment. You can refine all views after a generation. This is not a static image. Live, interactive analytics connected to your data.
Publish and share as a dashboard
If you are satisfied with the analysis, select it Publish creating a dashboard. You can share a dashboard with other users, embed it in apps within minutes with features like 1-click embedding, or schedule email delivery. The published dashboard stores all the sheets, visualizations, filter controls, and calculated fields from the generated analysis. Recipients interact with the dashboard without accessing the underlying analytics.
Getting started
At launch, Productivity Analytics is available to registered Enterprise/Author Pro users. Authors also have promotional access to this capability until December 2026 as part of Amazon Quick Enterprise, provided their organization has not restricted access. Available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), and Europe (London).
The conclusion
Generate Analytics on Amazon Quick creates comprehensive multi-page analytics from natural language input, reducing dashboard creation from hours to minutes. During early access, authors across functions, engineering, and data science reported reducing their dashboard creation time by 90% or more.
Another writer said: “As a new user, creating this dashboard would have taken at least a full day. It took 5 minutes.” – Prabhakant Rasal, SDE-III, PXT DLS Tech, Amazon, Dallas TX
AI builds your startup environment. You refine it and publish it as a dashboard. Dashboards code the questions your team needs to answer over and over again. For follow-up tests and one-on-one questions that arise in between, try Dataset Q&A to ask your data directly in natural language.
About the writers
