AWS Public Sector Blog

Tag: technical how-to

Creating satellite communications data analytics pipelines with AWS serverless technologies

Creating satellite communications data analytics pipelines with AWS serverless technologies

Satellite communications (satcom) networks typically offer a rich set of performance metrics, such as signal-to-noise ratio (SNR) and bandwidth delivered by remote terminals on land, sea, or air. Customers can use performance metrics to detect network and terminal anomalies and identify trends to impact business outcomes. This walkthrough presents an approach using serverless resources from AWS to build satcom control plane analytics pipelines. The presented architecture transforms the data to extract key performance indicators (KPIs) of interest, renders them in business intelligence tools, and applies machine learning (ML) to flag unexpected SNR deviations.

Announcing the AWS Well-Architected Operational Readiness Review lens

AWS announced the release of the Operational Readiness Review (ORR) program as a custom lens for the AWS Well-Architected Tool, which is designed to help you review the state of your applications and workloads against architectural best practices, identify opportunities for improvement, and track progress over time. Creating a custom lens for the Well-Architected Tool with the ORR program can help supplement Well-Architected reviews by including lessons learned that are specific to your business, culture, tools, and governance rules. Learn how to set up the ORR as a custom lens in this walkthrough.

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.

Getting started with Amazon Lightsail for Research: A tutorial using RStudio

Amazon Lightsail for Research is a new service that makes it simple to incorporate cloud computing resources into your work without cloud experience. With Lightsail for Research, you can shift large and/or time-consuming analysis from your laptop onto powerful cloud resources, run multiple analyses simultaneously, and continue computations even when your laptop is off or being used for other activities. In this blog post, learn how to use Lightsail for Research with a simple but common use case.

Supporting state agencies with Medicaid unwinding outreach: Creating a multi-lingual two-way messaging system

A key focus for the Department of Health and Human Services (HHS) and state Medicaid agencies is making sure those eligible for Medicaid maintain coverage and supporting transition to alternatives. Medicaid agencies need to conduct outreach to make their millions of members aware of the process for redetermination. With cloud-based tools from AWS, state agencies can conduct this outreach using no code/low code, serverless, elastic services that can scale to two billion text messages a day. In this blog post, learn how to set up a multi-lingual, interactive SMS message campaign that can automatically verify and update member information on file based on member responses.

Improving the customer experience for high-traffic public services: An architecture guidance

Improving the customer experience (CX) has emerged as an imperative for government agencies. In this blog post, learn an architecture pattern that public institutions can use to improve CX while building and deploying secure, resilient, and performant web applications that support sudden surges in demand for public services. This architecture pattern addresses the need of an example use case in which an agency must request information from thousands to millions of civilians, who may access a single-page application at similar times, and then sends email notifications to each civilian to confirm their activity.

Managing nonprofit members and donors with CiviCRM on AWS

Managing donors, members, and constituents is essential to the success of most nonprofits. Customer relationship management (CRM) systems, like the no-cost, nonprofit-focused CiviCRM, are an important part of this process. In this post, learn how to deploy CiviCRM using AWS, and explore an architecture for deploying CiviCRM in a way that is highly available and resilient to service disruptions or events.

How to build an Aadhaar Data Vault on AWS

An Aadhaar number is a 12-digit unique identification number issued by the Unique Identification Authority of India (UIDAI) to every individual in India. Considering the sensitivity of the Aadhaar number and the potential implication of having one’s Aadhaar number compromised, UIDAI mandated the need for all Aadhaar and Aadhaar-related data to be encrypted and stored separately in a secure, access-controlled data repository known as an Aadhaar Data Vault. This blog post explains how government and private entities that collect, process, and store Aadhaar data for various use cases can use AWS CloudHSM from AWS to create an Aadhaar data storage solution that can meet guidelines provided by UIDAI.

Predicting diabetic patient readmission using multi-model training on Amazon SageMaker Pipelines

Diabetes is a major chronic disease that often results in hospital readmissions due to multiple factors. An estimated $25 billion is spent on preventable hospital readmissions that result from medical errors and complications, poor discharge procedures, and lack of integrated follow-up care. If hospitals can predict diabetic patient readmission, medical practitioners can provide additional and personalized care to their patients to pre-empt this possible readmission, thus possibly saving cost, time, and human life. In this blog post, learn how to use machine learning (ML) from AWS to create a solution that can predict hospital readmission – in this case, of diabetic patients – based on multiple data inputs.

Visualize data lake address datasets on a map with Amazon Athena and Amazon Location Service geocoding

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.