Category: Analytics

In this post, we explore a comprehensive AWS architecture that transforms smart inhaler data into actionable clinical insights through real-time monitoring and advanced analytics. Healthcare organizations can leverage AWS IoT Core, Amazon MSK, and Amazon Redshift to build secure, scalable solutions that enable proactive respiratory care management and improved patient outcomes.

This blog post guides you through implementing a generative AI intelligent chatbot using Amazon Bedrock and AWS services, including developer lifecycle changes. It covers creating a scalable chatbot infrastructure with Terraform, using services like Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, OpenSearch Service, Lambda, Amazon S3, and IAM. The focus on IaC and automation brings key DevOps benefits: version control, consistent deployments, reduced errors, faster provisioning, and improved collaboration.

Learn about some common approaches for collecting data from multiple AWS services across your organization, including common patterns with code samples that you can reuse to consume the data.

This post is a hands-on companion to the Data Lake with SnapLogic on AWS Quick Start. See how to use a SnapLogic pipeline to transform your input data, load it into an Amazon Redshift data warehouse, query the data in Amazon Redshift, and visualize it with Amazon QuickSight, so that you can analyze the data.