AWS Big Data Blog

Category: Database

Integrating Amazon Kinesis, Amazon S3 and Amazon Redshift with Cascading on Amazon EMR

This is a guest post by Ryan Desmond, Solutions Architect at Concurrent. Concurrent is an AWS Advanced Technology Partner. With Amazon Kinesis developers can quickly store, collate and access large, distributed data streams such as access logs, click streams and IoT data in real-time. The question then becomes, how can we access and leverage this […]

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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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Building and Maintaining an Amazon S3 Metadata Index without Servers

Mike Deck is a Solutions Architect with AWS Amazon S3 is a simple key-based object store whose scalability and low cost make it ideal for storing large datasets. Its design enables S3 to provide excellent performance for storing and retrieving objects based on a known key. Finding objects based on other attributes, however, requires doing […]

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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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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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Building a Binary Classification Model with Amazon Machine Learning and Amazon Redshift

Guy Ernest is a Solutions Architect with AWS This post builds on Guy’s earlier posts Building a Numeric Regression Model with Amazon Machine Learning and Building a Multi-Class ML Model with Amazon Machine Learning. Many decisions in life are binary, answered either Yes or No. Many business problems also have binary answers. For example: “Is […]

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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. All of these provide opportunities for AWS customers to attend talks focused on big data and […]

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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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A Zero-Administration Amazon Redshift Database Loader

Ian Meyers is a Solutions Architecture Senior Manager with AWS With this new AWS Lambda function, it’s never been easier to get file data into Amazon Redshift. You simply push files into a variety of locations on Amazon S3 and have them automatically loaded into your Amazon Redshift clusters. Using AWS Lambda with Amazon Redshift […]

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