AWS Big Data Blog

Category: Analytics

Using AWS Lambda for Event-driven Data Processing Pipelines

awVadim Astakhov is a Solutions Architect with AWS Some big data customers want to analyze new data in response to a specific event, and they might already have well-defined pipelines to perform batch processing, orchestrated by AWS Data Pipeline. One example of event-triggered pipelines is when data analysts must analyze data as soon as it […]

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Persist Streaming Data to Amazon S3 using Amazon Kinesis Firehose and AWS Lambda

Derek Graeber is a Senior Consultant in Big Data Analytics for AWS Professional Services Streaming data analytics is becoming main-stream (pun intended) in large enterprises as the technology stacks have become more user-friendly to implement. For example, Spark-Streaming connected to an Amazon Kinesis stream is a typical model for real-time analytics. But one area that […]

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Automating Analytic Workflows on AWS

Wangechi Doble is a Solutions Architect with AWS Organizations are experiencing a proliferation of data. This data includes logs, sensor data, social media data, and transactional data, and resides in the cloud, on premises, or as high-volume, real-time data feeds. It is increasingly important to analyze this data: stakeholders want information that is timely, accurate, […]

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How Coursera Manages Large-Scale ETL using AWS Data Pipeline and Dataduct

This is a guest post by Sourabh Bajaj, a Software Engineer at Coursera. Coursera in their own words: “Coursera is an online educational startup with over 14 million learners across the globe. We offer more than 1000 courses from over 120 top universities.” At Coursera, we use Amazon Redshift as our primary data warehouse because […]

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Using BlueTalon with Amazon EMR

This is a guest post by Pratik Verma, Founder and Chief Product Officer at BlueTalon. Leonid Fedotov, Senior Solution Architect at BlueTalon, also contributed to this post. Amazon Elastic MapReduce (Amazon EMR) makes it easy to quickly and cost-effectively process vast amounts of data in the cloud. EMR gets used for log, financial, fraud, and […]

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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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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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