Tag: AWS Glue

Nonprofits can leverage the cloud to reduce the burden associated with their fundraising activities. With machine learning (ML), nonprofits can identify individuals who are more likely to engage and donate to their cause to support their mission. Read more to learn exactly how you can put these solutions into action and leverage ML to help your nonprofit with fundraising efforts. In this post, discover how to use Amazon Personalize to build a ML model that supports a wide-range of personalization experiences—without prior machine learning experience.

According to FAIR Health and the American Medical Association, telehealth use saw a nearly 3000% growth from pre-pandemic to during the pandemic. These services make virtual, real-time interactions between patient and provider possible. However, the great promise of telehealth has highlighted existing roadblocks that some face when trying to access healthcare in this country. The National Health IT Collaborative for the Underserved (NHIT) is a 501(c)3 non-profit organization on a mission to provide equitable access to health technologies and to make sure that these technologies address the needs of underserved communities and communities of color. Since its founding in 2008, NHIT has worked to advance health equity and economic viability on issues such as broadband access, electronic health records, precision medicine, consumer health applications and disaster resiliency.

Times Higher Education (THE) is a data-driven business that, with the help of AWS, is now realising the value of their data, which enables them to be better informed and make faster decisions for customers. THE provides a broad range of services to help set the agenda in higher education, and their insights help universities improve through performance analysis. THE worked with the AWS Data Lab to create a centralised repository of their data. Launching a data lake helped with providing a cost-effective platform and cataloguing data so they could understand their data and design new products to make use of it.

If you share data with other researchers, especially if they are using a different tool, you can quickly run into version issues, not knowing which file is the most current. Rather than sending data files everywhere, AWS offers a simple way to store your data in one central location so that you can read your data into SAS and still share it with other colleagues. In this blog post, I will explain how to export your data, store it in AWS, and query the data using SAS.

Serverless applications are typically discreet pieces of code that customers can use to manage security-related processes or stitch together multiple AWS services to solve a larger problem. They allow customers to build and run applications and services without dealing with infrastructure management tasks such as server or cluster provisioning, patching, operating system maintenance, and capacity provisioning. In this blog, I explain the serverless computing model, the Serverless Application Repository (SAR), solution constructs and implementations, why they matter to our government customers, and how they can use them to solve common problems.

Research computing has come a long way from the mainframes of the 1960s. At the recent Practice and Experience in Advanced Research Computing (PEARC) conference, I noted four emerging themes that underscore how the field continues to evolve.

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.

What if someone in a hospital room or public train station suddenly falls due to a stroke or other health issue? An automated monitoring system like AWS DeepLens, a deep learning-enabled video camera for developers, could detect such falls and contact emergency services in a timely manner. Using AWS DeepLens, I created a solution.

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.

Many local administrations deal with air pollution through the collection and analysis of air quality data. With AWS, cities can now create a serverless analytics solution using AWS Glue and AWS QuickSight for processing and analyzing a high volume of sensor data. This allows you to start quickly without worrying about servers, virtual machines, or […]