AWS Big Data Blog

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Extending Seven Bridges Genomics with Amazon Redshift and R

Christopher Crosbie is a Healthcare and Life Science Solutions Architect with Amazon Web Services The article was co-authored by Zeynep Onder, Scientist, Seven Bridges Genomics, an AWS Advanced Technology Partner. “ACTGCTTCGACTCGGGTCCA” That is probably not a coding language readily understood by many reading this blog post, but it is a programming framework that defines all […]

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Implementing Efficient and Reliable Producers with the Amazon Kinesis Producer Library

Kevin Deng is an SDE with the Amazon Kinesis team and is the lead author of the Amazon Kinesis Producer Library How do you vertically scale an Amazon Kinesis producer application by 100x? While it’s easy to get started with streaming data into Amazon Kinesis, streaming large volumes of data efficiently and reliably presents some […]

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Connecting R with Amazon Redshift

Markus Schmidberger is a Senior Big Data Consultant for AWS Professional Services Amazon Redshift is a fast, fully managed, scalable data warehouse (DWH) for PB of data. AWS customers are moving huge amounts of structured data into Amazon Redshift to offload analytics workloads or to operate their DWH fully in the cloud. Business intelligence and […]

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Running R on AWS

by Markus Schmidberger and Aaron Friedman | on | in Analytics* | Permalink | Comments |  Share

Many AWS customers already use the popular open-source statistic software R for big data analytics and data science. Other customers have asked for instructions and best practices for running R on AWS. Several months ago, I (Markus) wrote a post showing you how to connect R with Amazon EMR, install RStudio on the Hadoop master node, and use R […]

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Presto-Amazon Kinesis Connector for Interactively Querying Streaming Data

This is a guest post by Sivaramakrishnan Narayanan, Member of Technical Staff at Qubole, and Xing Quan, Director of Product Management at Qubole. Qubole is an AWS Advanced Technology Partner. Amazon Kinesis is a scalable and fully managed service for streaming large, distributed data sets. As applications (particularly on mobile and wearable devices) start to […]

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How Expedia Implemented Near Real-time Analysis of Interdependent Datasets

This is a guest post by Stephen Verstraete, a manager at Pariveda Solutions. Pariveda Solutions is an AWS Premier Consulting Partner. Common patterns exist for batch processing and real-time processing of Big Data. However, we haven’t seen patterns that allow us to process batches of dependent data in real-time. Expedia’s marketing group needed to analyze […]

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Large-Scale Machine Learning with Spark on Amazon EMR

This is a guest post by Jeff Smith, Data Engineer at Intent Media. Intent Media, in their own words: “Intent Media operates a platform for advertising on commerce sites.  We help online travel companies optimize revenue on their websites and apps through sophisticated data science capabilities. On the data team at Intent Media, we are […]

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Test drive two big data scenarios from the ‘Building a Big Data Platform on AWS’ bootcamp

Matt Yanchyshyn is a Sr. Manager for AWS Solutions Architecture AWS offers a number of events during the year such as our annual AWS re:Invent conference, the AWS Summit series, the AWS Pop-up Loft, and a variety of roadshows such as the upcoming AWS Big Data Solutions Days. All of these provide opportunities for AWS […]

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Indexing Common Crawl Metadata on Amazon EMR Using Cascading and Elasticsearch

Hernan Vivani is a Big Data Support Engineer for Amazon Web Services A previous post showed you how to get started with Elasticsearch and Kibana on Amazon EMR. In that post, we installed Elasticsearch and Kibana on an Amazon EMR cluster using bootstrap actions. This post shows you how to build a simple application with […]

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Using AWS Data Pipeline’s Parameterized Templates to Build Your Own Library of ETL Use-case Definitions

Leena Joseph is an SDE for AWS Data Pipeline In an earlier post, we introduced you to ETL processing using AWS Data Pipeline and Amazon EMR. This post shows how to build ETL workflow templates with AWS Data Pipeline, and build a library of recipes to implement common use cases. This is an introduction to […]

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