Category: Amazon QuickSight

Climate risk consists of transition risk and physical risk. Transition risk represents regulatory and market-based risks while physical climate risk covers climate-related earth processes and its effects on the built and natural environment. In this blog post, we highlight how to use Amazon Web Services (AWS) to enrich your asset portfolio with open climate data hosted in AWS.

Fleet managers can use Amazon Web Services (AWS) to ingest and analyze fleet driver data. In this post, we share how a large public transit agency in the United States worked with AWS to create a proof-of-concept (POC) to analyze operator behavior and improve its visibility of sudden acceleration-based events.

As the amount of health data increases, different healthcare, life sciences, population health, and public health organizations are working to modernize their data infrastructure, unify their data, and innovate faster with technologies like artificial intelligence and machine learning (AI/ML). In this blog post, we dive deep on architecture guidance that enables healthcare providers to improve patient care.

This walkthrough explores how to leverage Amazon Forecast to derive valuable business insights in satellite communications use-cases. Operations teams can quickly see accurate satellite capacity forecasts on a per beam basis. The benefits include lower cost via provisioning just the right amount of bandwidth, and a more streamlined customer experience since users will be less impacted by weather or surge events.

What if paper forms could be processed at the same speed as digital forms? What if their contents could be automatically entered in the same database as the digital forms? Medicaid agencies could analyze data in near real time and drive actionable insights on a single dashboard. By using artificial intelligence (AI) and machine learning (ML) services from AWS, Medicaid agencies can create this streamlined solution. In this walkthrough, learn how to extract, analyze, and interpret relevant information from paper-based Medicaid claims forms.

At AWS, many public sector customers operate fleets of vehicles (e.g. emergency response, public transportation) that generate location data, which is ultimately stored in a data lake. These customers frequently ask how they can quickly visualize this data and extract insights that can help them optimize how they operate their vehicle fleets. In this post, learn how to use Amazon Athena and Amazon Location Service to perform ad hoc reverse geocoding on a notional dataset of vehicle location history, and visualize the results on an Amazon QuickSight map.

Texas Region 4 ESC (TX-Region 4) is a regional education service center that offers a range of services that help K12 education organizations improve student performance, enable faculty success, and implement state initiatives. When TX-Region 4 wanted to migrate its business intelligence (BI) solution to the cloud, they turned to AWS and Amazon QuickSight to save time and produce more insights to better their educational offerings.

Easterseals, DC MD VA is a multifaceted nonprofit organization with the goal of enriching lives and expanding opportunities for children and adults in the Washington DC, Maryland, and Virginia (DMV) area, including people with disabilities and military backgrounds. With support from our account team at AWS, Easterseals established a data lake to better understand and define the impact our organization has on its participants with the overarching goal of empowering all people to to achieve their potential and live meaningful lives.

Many public sector customers in government, healthcare, and life sciences have data lakes that contain addresses (e.g., 123 Main Street). These customers frequently ask how they can quickly visualize these addresses on a geographic map to get a more intuitive understanding of how these addresses are distributed. In this post, learn how to use Amazon Athena and Amazon Location Service to perform ad hoc geocoding on an example dataset and visualize these geocoded addresses on an Amazon QuickSight map.

Data is an invaluable asset in the world of nonprofits. In this blog post, we offer a technical walkthrough to learn how nonprofits of all sizes can use Amazon QuickSight to quickly create interactive dashboards with the help of machine learning, providing a self-service way to effectively consume and analyze data without writing any code or having to worry about infrastructure.