Tag: AWS Lake Formation
Beginning on April 1, 2023, state Medicaid agencies (SMA) will have one year to “unwind” temporary COVID-era changes and return to pre-pandemic ways of working. A major part of that will be re-verifying that all 91 million members still qualify to receive Medicaid benefits. For nearly a year, AWS has supported SMAs with in-house Medicaid expertise to identify unwinding issues and develop solutions to address them. The top four concerns that SMAs have shared are in approaching outreach and engagement, staffing shortages, returned mail, and reporting capabilities. Learn how AWS can help states across the country overcome these challenges across different scenarios.
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.
Using data lakes, nonprofits can use data to influence strategy and inform decisions that produce value and impact. In this post, learn how to build a data lake, ingest data from a PostgreSQL server, give permissions to users to consume the data using AWS Lake Formation, and access and analyze the data using Amazon Athena.
Data lakes can help hospitals and healthcare organizations turn data into insights and maintain business continuity, while preserving patient privacy. A data lake is 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 to gain insights and guide better business decisions. In my previous post, “Getting started with a healthcare data lake,” I shared how to get started using data lakes in managing healthcare data and what a good “first sprint” architecture might look like. Here, I walk through building your first solution on AWS using a healthcare data lake as our example workload.
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.
If you are a scientific researcher, you are likely more interested in getting your research done than in the computational resources that you use to do it. You may think about ways to continue your research remotely with the rise in remote work. Did you know the cloud and Amazon Web Services (AWS) can accelerate your research and time to science? Here are five ways.