AWS Public Sector Blog

Tag: AWS Glue

Extracting, analyzing, and interpreting information from Medicaid forms with AWS

Extracting, analyzing, and interpreting information from Medicaid forms with AWS

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.

Optimizing your nonprofit mission impact with AWS Glue and Amazon Redshift ML

Nonprofit organizations focus on a specific mission to impact their members, communities, and the world. In the nonprofit space, where resources are limited, it’s important to optimize the impact of your efforts. Learn how you can apply machine learning with Amazon Redshift ML on public datasets to support data-driven decisions optimizing your impact. This walkthrough focuses on the use case for how to use open data to support food security programming, but this solution can be applied to many other initiatives in the nonprofit space.

Supporting health equity with data insights and visualizations using AWS

In this guest post, Ajay K. Gupta, co-founder and chief executive officer (CEO) of HSR.health, explains how healthcare technology (HealthTech) nonprofit HSR.health uses geospatial artificial intelligence and AWS to develop solutions that support improvements in healthcare and health equity around the world.

Analyzing vehicle fleet location data from a data lake with AWS

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.

Generating program-defining insights in seconds for child, adult, senior, and military services

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.

How to create a cybersecurity analytics platform with AWS analytics and machine learning

Cybersecurity analytics is a systematic methodology designed to collect, ingest, process, aggregate, and analyze security events. This methodology empowers organizations to proactively perform security investigations, powered by advanced analytics and machine learning (ML), which help mitigate cyber issues more effectively and efficiently at scale. Learn about the core components of a cybersecurity analytics framework and how organizations can use AWS to design a cybersecurity analytics platform with analytics and ML services.

Citi Logik helps governments drive action on transportation insights with AWS

Citi Logik is a UK-based government technology (GovTech) company and AWS Partner with Amazon Web Services (AWS). Citi Logik uses AWS to enhance anonymised raw mobile network data (MND) so organisations can identify trends in the flow of people across a variety of different transportation modes. Citi Logik provides their customers, including the West Yorkshire Combined Authority and Wiltshire County Council, with valuable insights to help them make informed decisions about future transportation planning and urban planning development.

Jacaranda Health advances maternal and infant health across Kenya and beyond with AWS

Jacaranda Health, a Kenya-based nonprofit organization, is on a mission to end preventable maternal and newborn deaths by deploying low-cost, sustainable solutions that improve the quality of care in government health systems. Jacaranda Health, a recipient of the 2021 AWS IMAGINE Grant award, uses AWS to power a health platform that uses artificial intelligence (AI) to connect mothers with timely information about pregnancy care, as well as potentially lifesaving advice and referrals to care facilities when it matters most.

How researchers at UC Davis support the swine industry with data analytics on AWS

A research team led by Dr. Beatriz Martinez Lopez at UC Davis supports pig farmers with a data analytics platform that aggregates and analyzes animal health data to diagnose animal viruses and diseases. But this platform was primarily designed for analysts and data scientists. To truly transform animal disease management, Martinez-Lopez wants to put this data analytics tool into the hands of farmers around the world. So the research team is using the scalable, cost-effective tools of the AWS Cloud, along with a research grant letter of support from AWS, to make this optimized platform a reality.

How Skillshare increased their click-through rate by 63% with Amazon Personalize

Skillshare is the largest global online learning community for creativity. They offer thousands of inspiring classes for creative and curious people on topics including illustration, design, photography, video, freelancing, and more. Skillshare wanted their members to easily discover relevant content with a seamless discovery process of personalized recommendations. Skillshare decided to test Amazon Personalize from AWS to make these data-fueled recommendations for members with machine learning. This blog post describes their Amazon Personalize solution architecture, their AWS Step Functions process, and the results of their experiment.