Category: Amazon Athena

Citizens are increasingly expecting government to provide modern digital experiences for conducting online transactions. Market research tells us 63 percent of consumers see personalization as the standard level of service. This post offers various architectural patterns for improving customer experience for the public sector for a wide range of use cases. The aim of the post is to help public sector organizations create customer experience solutions on the Amazon Web Services (AWS) Cloud using AWS artificial intelligence (AI) services and AWS purpose-built data analytics services.

In this post, we explore the complexities of data privacy and controls on Amazon Web Services (AWS), examine how creating a landing zone within which to contain such data is important, and highlight the differences between creating a landing zone from scratch compared with using the AWS Landing Zone Accelerator (LZA) for Healthcare. To aid explanation, we use a simple healthcare workload as an example. We also explain how LZA for Healthcare codifies HIPAA controls and AWS Security Best Practices to accelerate the creation of an environment to run protective health information workloads in AWS.

Amazon SageMaker is a fully managed machine learning (ML) service that provides various capabilities, including Jupyter Notebook instances. While RStudio, a popular integrated development environment (IDE) for R, is available as a managed service in Amazon Web Services (AWS) commercial Regions, it’s currently not offered in AWS GovCloud (US) Regions. Read this post, however, to learn how you can use SageMaker notebook instances with the R kernel to perform data analytics tasks in AWS GovCloud (US) Regions.

This post discusses how Amazon Web Services (AWS) can help you successfully set up an Amazon DataZone domain, aggregate data from multiple sources into a single centralized environment, and perform analytics on that data. Additionally, this post provides a sample architecture as well as a walkthrough on how to set up that architecture. Ultimately, this post serves as a valuable resource if you’re seeking to optimize your data management processes and derive actionable insights to drive business growth.

The Association of Schools and Programs of Public Health (ASPPH) — a nonprofit association with a vision for improved health and well-being for everyone, everywhere — partnered with Amazon Web Services (AWS) Professional Services (AWS ProServe) to move their curated data to a managed data lake on AWS. In this blog post, we share how ASPPH and AWS designed and built the data lake and the results of moving to a modern, scalable data architecture.

Healthcare authorities and providers use state-run controlled substance databases (CSDs) to track prescriptions and identify patients for substance abuse. CSDs help evaluate treatment options, screen patients who may be at risk for drug abuse problems, and make informed decisions about prescribing medication. This post explains how healthcare authorities can leverage CSD data to enhance their decision-making processes within business operations by using Amazon Web Services (AWS).

At the end of 2022, Northwestern University’s Kellogg School of Management had a decision to make. The on-premises SQL server used by faculty and students had reached the end of its life, and the school needed to identify a cost-effective way forward while ensuring that the datasets would remain highly available for researchers to use on demand. After weighing various options, Kellogg worked with Amazon Web Services (AWS) to create a data lake that fit its unique needs.

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.

Learn how the National Cancer Institute Imaging Data Commons (IDC) team migrated the Imaging Data Commons data to AWS using AWS DataSync. Plus, learn how to get started with IDC data, which is accessible at no cost through the AWS Open Data Sponsorship Program.