AWS Business Intelligence Blog
Category: Best Practices
Support multi-tenant applications for SaaS environments using Amazon QuickSight
This post provides guidance on deploying QuickSight in a multi-tenant environment, and the considerations around data isolation and deploying resources to tenants in a QuickSight application. Multi-tenancy within applications provides a mechanism to segment groups of users from one another. These groups could be users from different companies, different geographic regions, or different lines of business within an enterprise. Users within different tenants can’t see other users, data, and assets, while reducing the complexity of having a different infrastructure for each set of users.
Announcing QuickSight Arena: Explore Amazon QuickSight for free and showcase your dashboards
The Amazon QuickSight Community serves as a one-stop-shop where business intelligence (BI) authors and developers from across the globe can access learning content, ask and answer questions, stay up to date, network, and learn together about Amazon QuickSight. QuickSight powers data-driven organizations with unified BI at hyperscale. With QuickSight, all users can meet varying analytic needs from the same source of truth through modern interactive dashboards, paginated reports, embedded analytics, and natural language queries. In this post, we walk through the new QuickSight Arena—an embedded instance of QuickSight on the QuickSight Community—and explain its use cases and how to get started.
AWS recognized as a Strong Performer in The Forrester Wave: Augmented Business Intelligence Platforms, Q2 2023
AWS has been named a Strong Performer in the Forrester Wave’s 27-criterion evaluation of augmented business intelligence (BI) platforms providers for Q2 2023. Forrester evaluated 14 providers for their core BI features, ease of integration with machine learning, conversational UI, ease of use, and flexibility. Amazon QuickSight emerging as a Strong Performer validates for us […]
Unlock the power of unified business intelligence with Google Cloud BigQuery and Amazon QuickSight
Amazon QuickSight is a cloud-native, serverless business intelligence (BI) service that lets you build visualizations, perform ad hoc analysis, and gain insights through machine learning (ML) capabilities such as anomaly detection, forecasting, and natural language querying. QuickSight utilizes its robust in-memory engine SPICE (Super-fast, Parallel, In-memory Calculation Engine) to rapidly perform advanced calculations and deliver visuals.BigQuery is Google Cloud’s fully managed, petabyte-scale, cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near-real time. In this post, we walk you through the permissions and connection details needed in BigQuery to bring BigQuery data into QuickSight through OAuth and create a simple dashboard.
New enhancements in Amazon QuickSight: Programmatic export to Excel format
Amazon QuickSight is a scalable, serverless, embeddable, machine learning (ML)-powered business intelligence (BI) service built for the cloud. You can now export content to Excel workbooks by selecting multiple tables and pivot table visuals from any sheet of a dashboard on the QuickSight console via schedules or programmatically via a set of new Snapshot Export APIs. This post outlines these new functionalities and guides you through their implementation.
Deliver Amazon QuickSight pixel-perfect reports to non-QuickSight users
Amazon QuickSight Pixel-perfect Reports enables the creation and sharing of highly formatted, personalized reports containing business-critical data to hundreds of thousands of end-users without any infrastructure setup or maintenance, up-front licensing, or long-term commitments. In this post, we will cover how to use QuickSight, a serverless and cloud-native BI service, and Amazon Simple Storage Service (Amazon S3), an object storage service, to generate reports with specific parameters and have these reports delivered to users in a custom application.
Automate financial statements using Amazon QuickSight Snapshot Export APIs
Financial statements are a set of documents that contain formal records of financial activities of a business at a specific point in time. For example, a profit and loss (P&L) statement summarizes the revenues, expenses, and resulting net profit or loss of a business. It is a snapshot of the organization’s financial performance, starting from […]
Build and share a business capability model with Amazon QuickSight
The technology landscape has been evolving rapidly, with waves of change impacting IT from every angle. It is causing a ripple effect across IT organizations and shifting the way IT delivers applications and services. The change factors impacting IT organizations include: The shift from a traditional application model to a services-based application model (SaaS, PaaS) […]
Optimize queries using dataset parameters in Amazon QuickSight
Amazon QuickSight powers data-driven organizations with unified business intelligence (BI) at hyperscale. With QuickSight, all users can meet varying analytic needs from the same source of truth through modern interactive dashboards, pixel-perfect reports, embedded analytics and natural language queries. We have introduced dataset parameters, a new kind of parameter in QuickSight that can help you […]
Best practices for enabling business users to answer questions about data using natural language in Amazon QuickSight
In this post, we explain how you can enable business users to ask and answer questions about data using their everyday business language by using the Amazon QuickSight natural language query function, Amazon QuickSight Q. QuickSight is a unified BI service providing modern interactive dashboards, natural language querying, pixel-perfect reports, machine learning (ML) insights, and […]