AWS Big Data Blog

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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Building a Multi-Class ML Model with Amazon Machine Learning

Guy Ernest is a Solutions Architect with AWS This post builds on our earlier post Building a Numeric Regression Model with Amazon Machine Learning. We often need to assign an object (product, article, or customer) to its class (product category, article topic or type, or customer segment). For example, which category of products is most […]

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Optimizing for Star Schemas and Interleaved Sorting on Amazon Redshift

Chris Keyser is a Solutions Architect for AWS Many organizations implement star and snowflake schema data warehouse designs and many BI tools are optimized to work with dimensions, facts, and measure groups. Customers have moved data warehouses of all types to Amazon Redshift with great success. The Amazon Redshift team has released support for interleaved […]

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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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Building a Numeric Regression Model with Amazon Machine Learning

Guy Ernest is a Solutions Architect with AWS We need to predict future values in our businesses. These predictions are important for better planning of resource allocation and making other business decisions. Often, we settle for a simplified heuristic of average values from the past and some change assumption because more accurate alternatives are too […]

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Running a High Performance SAS Grid Manager Cluster on AWS with Intel Cloud Edition for Lustre

Chris Keyser is a Solutions Architect for Amazon Web Services This post was co-authored by Margaret Crevar, Sr. Manager, Performance Validation at SAS. SAS is an AWS Technology Partner. SAS (www.sas.com) is an integrated environment designed for business and advanced data analytics by enterprise and government organizations. SAS and AWS recently performed testing using the […]

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Nasdaq’s Architecture using Amazon EMR and Amazon S3 for Ad Hoc Access to a Massive Data Set

This is a guest post by Nate Sammons, a Principal Architect for Nasdaq The Nasdaq group of companies operates financial exchanges around the world and processes large volumes of data every day. We run a wide variety of analytic and surveillance systems, all of which require access to essentially the same data sets. The Nasdaq […]

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Processing Amazon Kinesis Stream Data Using Amazon KCL for Node.js

Manan Gosalia is an SDE for Amazon Kinesis This blog post shows you how to get started with the Amazon Kinesis Client Library (KCL) for Node.js. The Node.js framework uses an event-driven, non-blocking I/O model that makes it lightweight, efficient, and perfect for data-intensive, real-time applications that run across distributed devices. JavaScript is also simple […]

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Streaming Analytics with DataTorrent RTS and Amazon EMR

Nick Durkin is a Senior Solution Engineer for DataTorrent. DataTorrent is an AWS Technology Partner. In this blog post, we introduce fast big data and provide context about the DataTorrent RTS streaming analytics platform. In addition, we show you how to implement a real-time, streaming analytics application for capturing social media trends from Twitter using […]

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