Tag: Amazon QuickSight

Rideshare demand prediction is a well-explored topic in academia and industry, with abundant online resources offering diverse modeling frameworks tailored to different geographic contexts. A challenge with rideshare demand prediction, however, is that the trip data required to calibrate or train models can be exceptionally large. In this post, we explore the challenges of big data analytics and showcase how ArcGIS GeoAnalytics Engine, a spatial analytics library for the Apache Spark environment, can be used on Amazon EMR to effectively address these problems.

Like many healthcare providers, University Hospitals Coventry and Warwickshire (UHCW) NHS Trust, which manages two major hospitals and serves a population of more than one million, has operated with legacy technology that relies heavily on phone calls and manual processes for contacting patients. Recognizing an opportunity to modernize, the Trust linked up with IBM Consulting for an innovative pilot project to digitize patient engagement channels using Amazon Web Services (AWS). Read this post to learn more.

The Prosper Africa Tech for Trade Alliance is a collaboration uniting leading American and African tech companies behind the mission of accelerating e-commerce and digital trade in Africa. The recently announced collaboration between Amazon Web Services (AWS) and Choppies, a leading supermarket chain in Botswana, exemplifies the Alliance’s model of impact-oriented public-private partnerships. This post highlights the AWS-powered deployment of Choppies’ state-of-the-art Farmer’s app across its supplier network.

The Centers for Medicare & Medicaid Services (CMS) recently enabled states to extend Medicaid coverage to eligible incarcerated individuals, with hopes of ensuring continuity of care upon release, reducing the risk of relapse, and encouraging better health management. To help states begin benefitting from this new CMS policy, Amazon Web Services (AWS) offers a suite of data storage, telehealth, analytics, and reentry services. In this post, we break down four specific areas where AWS services—and AWS Partners—can help.

Healthcare organizations worldwide are leveraging Amazon Web Services (AWS) and partner solutions to modernize, transform, and innovate their businesses. Ensuring the availability and security of critical applications is paramount. For example, two renowned German medical facilities, Fachklinikum Mainschleife and Max Grundig Klinik, needed to modernize their IT infrastructure to comply with stringent regulatory requirements outlined in the country’s Law for Accelerating the Digitalization of Healthcare (DigiG). Reliable and compliant service offerings from AWS enabled the medical facilities to provide reliable access to essential systems.

In alignment with Singapore’s ambitious sustainability objectives, the Land Transport Authority (LTA) of Singapore is intensifying its efforts to spur the adoption of electric vehicles. This contributes to the nation’s goal of achieving 100 percent cleaner energy vehicles by 2040, and the effort leverages Amazon Web Services (AWS). LTA has set up EV-Electric Charging Pte Ltd (EVe) to manage the deployment of up to 12,000 electric vehicle (EV) charging points distributed across 2,000 Housing Development Board (HDB) carparks.

Cognitive Space is a leading Amazon Web Services (AWS) Partner delivering intelligent automation to satellite constellation operations using the CNTIENT platform. The system uses AWS-powered artificial intelligence (AI) decision making to handle highly complex and dynamic satellite tasking requirements, and demanding mission requirements. This blog post provides technical guidance for building and operating mission operation centers (MOCs) on AWS.

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.

In this post, you will learn how to deploy Amazon Web Services (AWS) Cloud Intelligence Dashboards (CID) using the Landing Zone Accelerator on AWS (LZA) solution. In doing so, you will learn how to customize your LZA deployment using the customizations-config.yaml file. By utilizing the LZA and CID together, you can streamline the deployment process, ensure compliance with best practices, and gain valuable insights into your cloud environment, ultimately leading to improved operational efficiency, enhanced security, and better-informed decision-making.