Tag: Data Lake

The COVID-19 Healthcare Coalition is a private-sector led response to COVID-19 that brings together healthcare organizations, technology firms, nonprofits, academia, and startups to preserve the healthcare delivery system and help protect U.S. populations. AWS is a member of the COVID-19 Healthcare Coalition, working side by side with leading healthcare providers and researchers such as the Mayo Clinic, Johns Hopkins, and ZocDoc. Together, we’re coordinating our collective expertise, capabilities, and data to provide insights to improve clinical outcomes.

Academic medical centers (AMCs) are under pressure to reduce costs, innovate at scale, and improve operational performance. To do this, they’re turning to the cloud. Two AWS Partner Network (APN) Public Sector Partners used the cloud to create solutions for AMCs that use large datasets to help advance medical research and analyze genomic data. Learn how these two partners are building solutions in the cloud to help AMCs further their mission.

Data related to healthcare, in both volume and variety, is undergoing a tremendous expansion. One of the best ways to tackle complicated data integration is through a data lake: a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake enables you to break down data silos and combine different types of analytics, such as data warehousing, big data processing, or operational analytics, to gain insights and guide better business decisions.

The rapidly changing and dynamic global health situation has impacted the lives of many people including researchers at universities and institutions worldwide. Many academic institutions are migrating to remote operations. Researchers are processing data, collaborating online, and trying to maintain labs remotely. Amazon and AWS are responding to these events in support of our communities and deploying resources and technology to enable remote learning and home working.

Cloud-based technology is supporting healthcare organisations and governments in response to the evolving COVID-19 situation. Healthcare providers and professionals, governments, and patients around the world are facing an unprecedented challenge. Here are some of the ways that these health-focused organisations use cloud-based technology to help improve patient services and outcomes.

In 2019, Grand River Hospital turned to AWS to build the first AWS healthcare data lake in Canada. The data lake was built to house the hospital’s sensitive patient and administrative data while retiring its legacy hospital information systems, comprised of electronic patient record and other administrative systems. Grand River Hospital in Ontario, Canada is a 580-bed community hospital with a yearly operating budget of around $400 million CAD serving a community of 600,000-650,000 people.

The botany department at the University of British Columbia (UBC) and the UBC Data Science Institute are working together to research the evolution and genetic makeup of sunflowers – a critical crop in addressing global food security.

Oklahoma State University in Oklahoma City (OSU-OKC), a two-year, technical-focused college, has historically faced challenges with consistent reporting, database management, and analytics. Technology generalists hired to do these tasks required extensive training to successfully extract data from traditional student information systems, manipulate data for state and federal compliance reporting, and generate limited campus reporting for operational or academic program review and analysis.

Virginia Tech wanted to build a modern data warehouse to complete new requests and quickly answer difficult questions in order to make more informed decisions. To do this, we turned to AWS. We were looking for a way to build forecasting models faster so we could quickly react to changing conditions.

Although more customers every day are using AWS to build, run and gain insights from data lakes, the journey to a data lake for many organizations can be one of uncertainty, and a path that may even seem too difficult to attempt. In this blog, we will discuss the challenges organizations can face with siloed data and how data from disparate systems can be brought together using data domains.