Tag: Amazon Redshift

Organizations deal with ever-growing data volumes. This means that growth-minded businesses must put data at the heart of every application, process, and decision. But how you use your organization’s data is the key to accelerating innovation and accomplishing your organizational goals.

Healthcare organizations across the nation are working to address clinician burnout and are more constrained than ever. That’s why Netsmart, an industry leader in electronic health records for human services and post-acute care, and Amazon Web Services joined forces to advance artificial intelligence for community-based care providers, through the development of an AI Data Lab. By combining the scale and power of AWS with the Netsmart CareFabric® platform, Netsmart is driving intelligent automation, generative AI, predictive analytics, natural language processing and risk models to improve care delivery and outcomes for community-based care providers.

There is power in data. Professors Monica Chiarini Tremblay and Rajiv Kohli at William & Mary’s Raymond A. Mason School of Business detail how Carlos Rivero, the former chief data officer of the Commonwealth of Virginia, created a foundation for data sharing in Virginia powered by multiple AWS solutions.

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.

Cybersecurity analytics is a systematic methodology designed to collect, ingest, process, aggregate, and analyze security events. This methodology empowers organizations to proactively perform security investigations, powered by advanced analytics and machine learning (ML), which help mitigate cyber issues more effectively and efficiently at scale. Learn about the core components of a cybersecurity analytics framework and how organizations can use AWS to design a cybersecurity analytics platform with analytics and ML services.

Advances in technology are transforming the way health research can be conducted. It is now possible to integrate data from siloed sources into a data lake, a central repository where health data are aggregated and analyzed at scale. Now, more than ever, there are opportunities for collaborative research to accelerate life-saving medical innovation – and that’s exactly what JDRF International, the leading global Type 1 Diabetes research and advocacy organization, is doing with AWS.

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.

Forrester estimates that data-driven businesses are growing at an average of more than 30 percent annually. This is also happening at education technology companies. With new data sources have emerging, including real-time streaming data from virtual classrooms, mobile engagement, unique usage, and new learners, these data sources are shaping the next generation of EdTech products that engage learners meaningfully around the world. Learn how four AWS EdStart Members are utilizing data to power their solutions.

Skillshare is the largest global online learning community for creativity. They offer thousands of inspiring classes for creative and curious people on topics including illustration, design, photography, video, freelancing, and more. Skillshare wanted their members to easily discover relevant content with a seamless discovery process of personalized recommendations. Skillshare decided to test Amazon Personalize from AWS to make these data-fueled recommendations for members with machine learning. This blog post describes their Amazon Personalize solution architecture, their AWS Step Functions process, and the results of their experiment.