Extracting insights from extensive datasets is essential across various sectors, including life sciences. To address the increasing costs associated with drug development, pharmaceutical companies are seeking innovative methods to enhance their drug discovery processes. They are leveraging big data analytics to more accurately assess the impacts of their drug compounds. For further insights, check out this other blog post here.
Developing a Serverless Framework to Analyze Amazon CloudFront Access Logs Using AWS Lambda, Amazon Athena, and Amazon Kinesis Analytics
by Mark Thompson, Chris Geisel, and Priya Sharma
on 26 MAY 2017
in Amazon Athena, Amazon CloudFront, Amazon Kinesis, AWS Big Data, AWS Lambda
In today’s digital landscape, it is common for web servers to be supported by global content delivery networks such as Amazon CloudFront. This setup enhances the delivery speed of websites, APIs, media content, and other digital assets, providing users with a superior experience worldwide. The analyses conducted on Amazon CloudFront access logs can yield valuable insights, as noted by experts at this authority.
Constructing a Healthcare Data Warehouse with Amazon EMR, Amazon Redshift, AWS Lambda, and OMOP
by Kevin Wright
on 12 MAY 2017
in Amazon EMR, Amazon Redshift, Analytics, AWS Big Data, AWS Lambda
In healthcare, data manifests in numerous formats. Despite attempts to standardize terminology, certain concepts, like blood glucose levels, are often represented inconsistently. This article illustrates how to transform an openly accessible dataset known as MIMIC-III, which contains de-identified medical information for approximately 40,000 patients, into an open-source data model.
How Eliza Corporation Transitioned Healthcare Data to the Cloud
by NorthBay Solutions
on 06 OCT 2016
in Amazon EMR, AWS Big Data, AWS Lambda
This piece addresses the practical obstacles encountered during the implementation of a data lake for Eliza, detailing the methods we employed to overcome these challenges with AWS. The issues stemmed from data variety and the necessity for a unified view of the data. For more practical insights on AWS, this Reddit thread is an excellent resource.
Establishing Event-Driven Batch Analytics on AWS
by Nathan Reed
on 04 OCT 2016
in Amazon EMR, AWS Big Data, AWS Lambda
In this article, I guide you through an architectural strategy along with a sample implementation for collecting, processing, and analyzing data for event-driven applications in the AWS environment.
Analyzing VPC Flow Logs with Amazon EMR
by Lisa Grant
on 02 SEP 2016
in Amazon EMR, AWS Big Data, AWS Lambda
This post demonstrates how to extract meaningful insights from your network by utilizing Amazon EMR and Amazon VPC Flow Logs. The guide implements a common networking pattern referred to as ‘Top Talkers’—an ordered list of the most significant network users—though the model is adaptable for various types of network analysis.
Streamlining Amazon Redshift Snapshot Management with AWS Lambda
by Ethan Clark
on 15 JUL 2016
in Amazon Redshift, Analytics, AWS Big Data, AWS Lambda
NOTE: Amazon Redshift now features automatic snapshot scheduling via the snapshot scheduler. For additional details, refer to this “What’s New” post. Ian Meyers, a Solutions Architecture Senior Manager with AWS, explains how Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that simplifies and reduces costs for analyzing all your data.
Real-time In-Memory OLTP and Analytics with Apache Ignite on AWS
by Sarah Williams
on 14 MAY 2016
in Amazon DynamoDB, Amazon Kinesis, Amazon Redshift, Analytics, AWS Big Data, AWS Lambda
As of February 9, 2024, Amazon Kinesis Data Firehose has been rebranded as Amazon Data Firehose. Refer to the AWS “What’s New” post for further information. Babu Elumalai, a Solutions Architect at AWS, discusses how organizations are generating vast amounts of data and the increasing necessity for tools and systems that assist them in utilizing this data for decision-making.
From SQL to Microservices: Integrating AWS Lambda with Relational Databases
by David Reynolds
on 05 MAY 2016
in AWS Big Data, AWS Lambda
Bob Strahan, a Senior Consultant with AWS Professional Services, highlights how AWS Lambda has emerged as a powerful compute platform, enabling seamless integration with relational databases to enhance performance and scalability.
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