Category: Analytics

Although it’s common for Amazon EMR customers to process data directly in Amazon S3, there are occasions where you might want to copy data from S3 to the Hadoop Distributed File System (HDFS) on your Amazon EMR cluster. Additionally, you might have a use case that requires moving large amounts of data between buckets or regions. In these use cases, large datasets are too big for a simple copy operation.

In April, we announced Amazon Redshift Spectrum in the AWS Blog. Redshift Spectrum is a new feature of Amazon Redshift that allows you to run complex SQL queries against exabytes of data in Amazon without having to load and transform any data. We’re happy to announce that Amazon QuickSight now supports Redshift Spectrum. Starting today, […]

Nowadays, it’s common for a web server to be fronted by a global content delivery service, like Amazon CloudFront. This type of front end accelerates delivery of websites, APIs, media content, and other web assets to provide a better experience to users across the globe. The insights gained by analysis of Amazon CloudFront access logs […]

Since launch, Amazon QuickSight has enabled business users to quickly and easily analyze data from a wide variety of data sources with superfast visualization capabilities enabled by SPICE (Superfast, Parallel, In-memory Calculation Engine). When setting up Amazon QuickSight access for business users, administrators have a choice of authentication mechanisms. These include Amazon QuickSight–specific credentials, AWS […]

April 2024: The solution presented in this post is deprecated. Customers across the world are increasingly building innovative Internet of Things (IoT) workloads on AWS. With AWS, they can handle the constant stream of data coming from millions of new, internet-connected devices. This data can be a valuable source of information if it can be […]

In the healthcare field, data comes in all shapes and sizes. Despite efforts to standardize terminology, some concepts (e.g., blood glucose) are still often depicted in different ways. This post demonstrates how to convert an openly available dataset called MIMIC-III, which consists of de-identified medical data for about 40,000 patients, into an open source data […]

October 2024: This post was reviewed and updated for accuracy. When building a streaming data solution, most customers want to test it with data that is similar to their production data. Creating this data and streaming it to your solution can often be the most tedious task in testing the solution. Amazon Kinesis Data Streams […]

Starting with Amazon EMR 5.2.0, you have the option to run Apache HBase on Amazon S3. Running HBase on S3 gives you several added benefits, including lower costs, data durability, and easier scalability. HBase provides several options that you can use to migrate and back up HBase tables. The steps to migrate to HBase on […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Last December, we introduced the Amazon Athena connector in Amazon QuickSight, in the Derive Insights from IoT in Minutes using AWS IoT, Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight post. The […]

We launched Amazon QuickSight to democratize BI. Our goal is to make it easier and cheaper to roll out advanced business analytics capabilities to everyone in an organization. Overall, this enables better understanding of business, and allows faster data-driven decisions in an organization. In the past, the ability to share data presented an administrative challenge […]