Category: Amazon QuickSight

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.

The Amazon Web Services (AWS) Resilience Hub provides you with a single place to define your resilience goals, assess your resilience posture against those goals, and implement recommendations for improvement. In this post, we discuss how we can track the resiliency of software applications and infrastructure using AWS Resilience Hub to provide “always available” services and monitor changes to the application availability.

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.

Amazon Web Services (AWS) employs project management principles to deliver public sector cloud outcomes. These principles drive successful service launches, new solutions, and workload migrations. Read this blog post to learn about the project management tools, references, and AWS Management Console tips that give public sector customers better project visibility, automate task management, and help accelerate project outcomes.

Funding sources for education technology (EdTech) companies slowed down in 2023. EdTech leaders must strike the right balance of investment to drive growth, and a return on investment for their owners. Read this blog post for an outline of the profitability framework that Amazon Web Services (AWS) uses with customers. The framework helps EdTechs improve cost efficiency, assess functionality expansion, and grow market share.

Amazon Web Services (AWS) made more than 140 announcements at re:Invent 2023. In this blog post, we’ll take key announcements from re:Invent and apply them to relevant K12 education use cases. From generative artificial intelligence (AI) to cost optimization, AWS can support your school, district, or educational service agency and enhance both the classroom and administrative experience. 

To improve safety and convenience, transportation agencies amass a substantial volume of data. However, these organizations encounter challenges in data accuracy validation due to issues related to data quality and occasional missing information. With the incorporation of new artificial intelligence and machine learning capabilities from Amazon Web Services (AWS), they can take advantage of no-code solutions to identify and address data gaps.

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.