Category: Technical How-to

In this post, we demonstrate the new console and dashboard embedding features available in Amazon QuickSight, using Amazon Q.

We’ve heard from customers that analyzing user activity and understanding usage patterns has been challenging. Common questions include “How many Reader Pro licenses have we added in the last 90 days?” and “What’s our actual session consumption pattern?” To address these needs, we’re excited to share a solution that makes it easier than ever to gain insights into your QuickSight usage and make data-driven decisions about your BI implementation.

In this post, we demonstrate how to use Amazon Bedrock model invocation logs to enhance the observability of model usage by using Amazon Athena for efficient log querying and Amazon QuickSight for insightful visualizations.

In this post we discuss the process of creating a comprehensive view of AWS Network Firewall logs using Amazon QuickSight. We explain the steps and resources to construct a tailored analytics dashboard within QuickSight, enabling a better understanding of network events and traffic patterns. This approach aids in identifying anomalies, threats, and network events with fine-grained insights during troubleshooting.

Many organizations use OneLogin as their identity provider (IdP) to control and manage user authentication and authorization centrally. Amazon QuickSight can integrate with OneLogin through the use of single sign-on (SSO) and SAML 2.0 authentication. With this integration, users can access QuickSight using their existing OneLogin credentials, providing a seamless and secure authentication experience. In this post, we walk you through the steps to configure federated SSO to QuickSight with OneLogin as your IdP.

In this post, we discuss how you are now able to bring unstructured data from Amazon Q Business into QuickSight Q&A to ask questions about your data and obtain relevant insights from your company documents as well as get enriched insights in data stories.

In this post, we explore how to create a simple serverless architecture using AWS Lambda, Amazon Athena, and QuickSight to establish column level lineage. Tracking column-level lineage provides a clear view of each column’s path through different parts of QuickSight, helping to optimize data processing, improve query performance, ensure accuracy, and meet regulatory requirements.

This blog post shows how data owners and business intelligence (BI) administrators can centrally manage fine-grained data permissions on Amazon Redshift tables and views and enforce them on all users in Amazon QuickSight with AWS IAM Identity Center trusted identity propagation.

Amazon QuickSight is a cloud-powered, serverless, and embeddable business intelligence (BI) service that makes it straightforward to deliver insights to everyone in your organization. As a fully managed service, QuickSight lets you create and publish interactive dashboards that can then be accessed from any device and embedded into your applications, portals, and websites. QuickSight is expanding filter and control functionality. Previously, a filter could be scoped to a single visual, some visuals, all of the visuals for a dataset on a sheet, or all applicable visuals on a sheet. With the launch of cross-sheet filters and controls, authors can now create, delete, and edit filters that apply to multiple sheets. Previously, cross-sheet filters could be created with parameters in over forty clicks. With the expansion in functionality, they can be created in just five clicks, which shows how much this new feature simplifies setting up filters and controls that impact multiple sheets.

Amazon QuickSight stands at the forefront of AWS business intelligence (BI) and data visualization offerings, enabling organizations to create and share interactive dashboards, perform one-time analyses, and glean actionable insights from their data. In today’s data-centric business environment, the ability to efficiently generate and distribute insightful reports across different segments or regions remains a critical challenge for many business. Addressing this challenge, we delve into the automation of report processing workflows. For our use case, a real estate customer wants to send state-specific weekly real estate reports for each state to their regional agents. In this post, we show you how to use QuickSight, combined with its Snapshot APIs and other AWS services, to automate this process.