Tag: AWS DMS

Organizations require solutions for real time or near real time dashboards that can be provided to their customers without impacting their database performance or service level agreements (SLAs) to their end users. In this post, we showcase the integration of Amazon Web Services (AWS) capabilities to present an end-to-end architecture for this data flow.

Earlier this year, the Australian Bureau of Statistics (ABS) ran the Australian Census, the agency’s most significant workload, on Amazon Web Services (AWS). The Census is the most comprehensive snapshot of the country, and includes around 10 million households and over 25 million people. With the COVID-19 pandemic causing lockdowns across the country, ABS needed a digital option for the Census that was accessible and reliable for millions of people. They turned to the cloud.

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.

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.

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.