Amazon QuickSight Blogs

Introduction: data modernization challenges and on-premises solutions in the power industry In the power industry, modernizing data infrastructure is especially challenging due to strict cybersecurity mandates, data residency rules, and the need for real-time reliability. Furthermore, energy systems are inherently hybrid. They rely on a distributed patchwork of OEMs, protocols, and on-premises infrastructure, often in [...]

Amazon QuickSight powers data-driven organizations with unified business intelligence (BI) at hyperscale. With Amazon Q in QuickSight, business analysts and business users can use natural language to build, discover, and share meaningful insights in seconds, turning insights into impact faster. Join us for online and in-person events in June 2025.

Organizations managing large audio and video archives face significant challenges in extracting value from their media content. Consider a radio network with thousands of broadcast hours across multiple stations and the challenges they face to efficiently verify ad placements, identify interview segments, and analyze programming patterns. In this post, we demonstrate how you can automatically transform unstructured media files into searchable, analyzable content.

In this post, we discuss how the NFL succeeded in delivering insights to fans at scale with QuickSight through two groundbreaking experiences: Combine IQ and Draft IQ. These experiences transformed NFL’s talent evaluation events by providing insights on player performance and draft predictions to over 1.14 million visitors and to millions of fans viewing broadcasts worldwide.

When was the last time you found yourself trying to look at rows and rows of data in a spreadsheet struggling to interpret and draw conclusions? Many analysts and engineers experience the same challenge every day. Whether it’s analyzing sales trends, monitoring operational metrics, or understanding customer behavior, the challenge lies not just in interpreting [...]

Mid-Hudson Valley Federal Credit Union (MHVFCU) needed to automate their tools and develop advanced forecasting capabilities to make informed decisions for deposit management and growth to maximize benefit for their members. For this purpose, MHVFCU leadership sought a solution that would not only save time in data preparation and analysis but also provide accurate forecasts for balances across four key deposit products: savings, checking, certificate deposits (CDs), and money market. Read this post to learn about the solution they built with AWS.

In this post, we explore how Principal used this opportunity to build an integrated voice VA reporting and analytics solution using an Amazon QuickSight dashboard.

This post offers a solution for monitoring and analyzing QuickSight datasets by providing valuable insights for efficient QuickSight usage and maintenance using a custom QuickSight dashboard. The solution provides a comprehensive view of SPICE ingestion status and type, SPICE usage metrics along with total capacity limit for the account, dataset relationships with dashboards, analyses, and linked data sources along with dataset query mode.

In this post, Opendoor shares how they transformed their business intelligence capabilities by migrating from a legacy SQL-centric tool to Amazon QuickSight, resulting in 80% cost savings, faster dashboard performance, and increased data accessibility across their organization while enabling self-service analytics for non-technical users.

In this post, we show how to seamlessly integrate Amazon CloudWatch logs with QuickSight using the Amazon Athena connector. With this integration, you can use your CloudWatch logs directly within the intuitive and feature-rich QuickSight environment, thereby unlocking deeper insights and streamlined workflows.

Note: This post references the use of multi-tenant or shared distributions, which has recently released more formalized support through SaaS Manager for CloudFront. Check out the latest blog to see how multiple domain delivery can leverage SaaS Manager. Amazon CloudFront is the AWS native Content Delivery Network (CDN) that reduces latency, improves availability, and secures [...]

In this post, we show you how Amazon Q Business can help augment your generative AI needs in all the abovementioned use cases and more by answering questions, providing summaries, generating content, and securely completing tasks based on data and information in your enterprise systems.

In this post, we explore how QuickSight generative BI can help you extract meaningful insights from your custom Jira projects. We demonstrate practical use cases, showcase the technology’s capabilities, and provide guidance on how to implement this solution in your environment.

In April 2025, AWS added carbon emissions data to AWS Data Exports. This managed feature introduces the ability to automatically export carbon emissions data with AWS Account and AWS Region granularity on a monthly basis to Amazon Simple Storage Service (S3). When using AWS Organizations, the carbon emissions export delivers data for all member accounts linked to your management account. This blog post explains how to configure the recurring delivery of carbon emissions data to Amazon S3 and visualize the exported data in the sustainability-proxy-metrics dashboard of the Cloud Intelligence Dashboards (CID). Utilizing Data Exports and the CID, you can track emissions across more than one AWS organization, with the ability to build custom visualizations and drill down to member account-level granularity.

Pendulum is an AI-powered analytics platform that aggregates and analyzes real-time data from social media, news, and podcasts. Designed to help organizations stay ahead, it enables reputation monitoring, early crisis detection, and influencer activity tracking. Using machine learning (ML) enables Pendulum to surface key insights from multiple channels, providing a comprehensive view of the digital [...]