AWS Big Data Blog

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Rapid-7 Multi-tenant Architecture

How Rapid7 built multi-tenant analytics with Amazon Redshift using near-real-time datasets

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. This is a guest post co-written by Rahul Monga, Principal Software Engineer at Rapid7. Rapid7 InsightVM is a vulnerability assessment and management product that provides visibility into the risks present across an […]

How MOIA built a fully automated GDPR compliant data lake using AWS Lake Formation, AWS Glue, and AWS CodePipeline

This is a guest blog post co-written by Leonardo Pêpe, a Data Engineer at MOIA. MOIA is an independent company of the Volkswagen Group with locations in Berlin and Hamburg, and operates its own ride pooling services in Hamburg and Hanover. The company was founded in 2016 and develops mobility services independently or in partnership […]

Create a custom Amazon S3 Storage Lens metrics dashboard using Amazon QuickSight

Companies use Amazon Simple Storage Service (Amazon S3) for its flexibility, durability, scalability, and ability to perform many things besides storing data. This has led to an exponential rise in the usage of S3 buckets across numerous AWS Regions, across tens or even hundreds of AWS accounts. To optimize costs and analyze security posture, Amazon […]

How Magellan Rx Management used Amazon Redshift ML to predict drug therapeutic conditions

This post is co-written with Karim Prasla and Deepti Bhanti from Magellan Rx Management as the lead authors. Amazon Redshift ML makes it easy for data scientists, data analysts, and database developers to create, train, and use machine learning (ML) models using familiar SQL commands in Amazon Redshift data warehouses. The ML feature can be […]

How Comcast uses AWS to rapidly store and analyze large-scale telemetry data

This blog post is co-written by Russell Harlin from Comcast Corporation. Comcast Corporation creates incredible technology and entertainment that connects millions of people to the moments and experiences that matter most. At the core of this is Comcast’s high-speed data network, providing tens of millions of customers across the country with reliable internet connectivity. This […]

How GE Healthcare modernized their data platform using a Lake House Architecture

GE Healthcare (GEHC) operates as a subsidiary of General Electric. The company is headquartered in the US and serves customers in over 160 countries. As a leading global medical technology, diagnostics, and digital solutions innovator, GE Healthcare enables clinicians to make faster, more informed decisions through intelligent devices, data analytics, applications, and services, supported by […]

Synchronize and control your Amazon Redshift clusters maintenance windows

Amazon Redshift is a data warehouse that can expand to exabyte-scale. Today, tens of thousands of AWS customers (including NTT DOCOMO, Finra, and Johnson & Johnson) use Amazon Redshift to run mission-critical business intelligence dashboards, analyze real-time streaming data, and run predictive analytics jobs. Amazon Redshift powers analytical workloads for Fortune 500 companies, startups, and […]

How Takeda uses the GraphQL API with AWS AppSync to support data scientists

This is a guest blog post by Michael Song and Rajesh Mikkilineni at Takeda. In their own words, “Takeda is a global, values-based, R&D-driven biopharmaceutical leader committed to discover and deliver life-transforming treatments, guided by our commitment to patients, our people and the planet. Takeda’s R&D data engineering team aspires to build a robust and […]

How JPMorgan Chase built a data mesh architecture to drive significant value to enhance their enterprise data platform

April 2024: This post was reviewed for accuracy. This is a joint blog post co-authored with Anu Jain, Graham Person, and Paul Conroy from JP Morgan Chase.  Most modern organizations recognize that their data benefits their entire enterprise. Data has value to the individual business process that produces it, but data’s additional potential can be […]

Amazon Redshift announces general availability of support for JSON and semi-structured data processing

At AWS re:Invent 2020, we announced the preview of native support for JSON and semi-structured data in Amazon Redshift. This includes a new data type, SUPER, which allows you to store JSON and other semi-structured data in Amazon Redshift tables, and support for the PartiQL query language, which allows you to seamlessly query and process […]