Category: Amazon Redshift
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.
In this blog post, learn a high-level architecture, built on AWS, that uses a graph database to analyze unstructured and structured educational data that can, for example, help inform a recommendation to a student for the appropriate courses to take in their next semester based on multiple personalized data factors.
Data lakes are becoming increasingly common in many different workloads, and geospatial is no exception. In 2021, Amazon Web Services (AWS) announced geography and geohash support on Amazon Redshift, so geospatial analysts have the capability to quickly and efficiently query geohashed vector data in Amazon Simple Storage Service (Amazon S3). In this blog post, I walk through how to use geohashing with Amazon Redshift partitioning for quick and efficient geospatial data access, analysis, and transformation in your data lake.
Join us at the upcoming AWS Public Sector Summit Online (April 15-16, 2021) where attendees will have the opportunity to test their knowledge and learn new skills in the AWS Jam Lounge and virtual workshops. Put your skills to the test in the AWS Jam Lounge (Sponsored by Intel and Fortinet) and learn something new by attending virtual workshops