Category: Analytics

Human Longevity, Inc. (HLI) is at the forefront of genomics research and wants to build the world’s largest database of human genomes along with related phenotype and clinical data, all in support of preventive healthcare. In today’s guest post, Yaron Turpaz, Bryan Coon, and Ashley Van Zeeland talk about how they are using AWS to […]

After a preview period that included participants from over 1,500 AWS customers ranging from startups to global enterprises, I am happy to be able to announce that Amazon QuickSight is now generally available! When I invited you to join the preview last year, I wrote: In the past, Business Intelligence required an incredible amount of […]

Amazon Simple Email Service (SES) focuses on deliverability – getting email through to the intended recipients. In my launch blog post (Introducing the Amazon Simple Email Service), I noted that several factors influence delivery, including the level of trust that you have earned with multiple Internet Service Providers (ISPs) and the number of complaints and […]

Our customers use Amazon EMR (including Apache Hadoop and the full range of tools that make up the Apache Spark ecosystem) to handle many types of mission-critical big data use cases. For example: Yelp processes over a terabyte of log files and photos every day. Expedia processes streams of clickstream, user interaction, and supply data. […]

In today’s guest post, Anton Slutsky of MeetMe describes the implementation process for their Data Lake. — Jeff; Anton Slutsky is an experienced information technologist with nearly two decades of experience in the field. He has an MS in Computer Science from Villanova University and a PhD in Information Science from Drexel University. Modern Big […]

Many AWS customers have been asking us for a way to programmatically analyze their Cost and Usage Reports (read New – AWS Cost and Usage Reports for Comprehensive and Customizable Reporting for more info). These customers are often using AWS to run multiple lines of business, making use of a wide variety of services, often […]

As you may know, Amazon Kinesis greatly simplifies the process of working with real-time streaming data in the AWS Cloud. Instead of setting up and running your own processing and short-term storage infrastructure, you simply create a Kinesis Stream or Kinesis Firehose, arrange to pump data in to it, and then build an application to […]

The Amazon EMR team has been cranking out new releases at a fast and furious pace! Here’s a quick recap of this year’s launches: EMR 4.7.0 – Updates to Apache Tez, Apache Phoenix, Presto, HBase, and Mahout (June). EMR 4.6.0 – HBase for realtime access to massive datasets (April). EMR 4.5.0 – Updates to Hadoop, […]

Amazon EMR allows you to quickly and cost-effectively process vast amounts of data. Since the 2009 launch, we have added many new features and support for an ever-increasing roster of applications from the Hadoop ecosystem. Here are a few of the additions that we have made this year: April – Support for Apache HBase 1.2 […]

Apache HBase is a distributed, scalable big data store designed to support tables with billions of rows and millions of columns. HBase runs on top of Hadoop and HDFS and can also be queried using MapReduce, Hive, and Pig jobs. AWS customers use HBase for their ad tech, web analytics, and financial services workloads. They […]