AWS Big Data Blog

Category: Analytics*

Derive Insights from IoT in Minutes using AWS IoT, Amazon Kinesis Firehose, Amazon Athena, and Amazon QuickSight

Ben Snively is a Solutions Architect with AWS Speed and agility are essential with today’s analytics tools. The quicker you can get from idea to first results, the more you can experiment and innovate with your data, perform ad-hoc analysis, and drive answers to new business questions. Serverless architectures help in this respect by taking […]

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Run Jupyter Notebook and JupyterHub on Amazon EMR

Tom Zeng is a Solutions Architect for Amazon EMR Jupyter Notebook (formerly IPython) is one of the most popular user interfaces for running Python, R, Julia, Scala, and other languages to process and visualize data, perform statistical analysis, and train and run machine learning models. Jupyter notebooks are self-contained documents that can include live code, […]

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Respond to State Changes on Amazon EMR Clusters with Amazon CloudWatch Events

Jonathan Fritz is a Senior Product Manager for Amazon EMR Customers can take advantage of the Amazon EMR API to create and terminate EMR clusters, scale clusters using Auto Scaling or manual resizing, and submit and run Apache Spark, Apache Hive, or Apache Pig workloads. These decisions are often triggered from cluster state-related information. Previously, […]

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Building an Event-Based Analytics Pipeline for Amazon Game Studios’ Breakaway

All software developers strive to build products that are functional, robust, and bug-free, but video game developers have an extra challenge: they must also create a product that entertains. When designing a game, developers must consider how the various elements—such as characters, story, environment, and mechanics—will fit together and, more importantly, how players will interact […]

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Using SaltStack to Run Commands in Parallel on Amazon EMR

Miguel Tormo is a Big Data Support Engineer in AWS Premium Support Amazon EMR provides a managed Hadoop framework that makes it easy, fast, and cost-effective to process vast amounts of data across dynamically scalable Amazon EC2 instances. Amazon EMR defines three types of nodes: master node, core nodes, and task nodes. It’s common to […]

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Joining and Enriching Streaming Data on Amazon Kinesis

Are you trying to move away from a batch-based ETL pipeline? You might do this, for example, to get real-time insights into your streaming data, such as clickstream, financial transactions, sensor data, customer interactions, and so on.  If so, it’s possible that as soon as you get down to requirements, you realize your streaming data […]

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Interactive Analysis of Genomic Datasets Using Amazon Athena

Aaron Friedman is a Healthcare and Life Sciences Solutions Architect with Amazon Web Services The genomics industry is in the midst of a data explosion. Due to the rapid drop in the cost to sequence genomes, genomics is now central to many medical advances. When your genome is sequenced and analyzed, raw sequencing files are […]

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Implementing Authorization and Auditing using Apache Ranger on Amazon EMR

Role-based access control (RBAC) is an important security requirement for multi-tenant Hadoop clusters. Enforcing this across always-on and transient clusters can be hard to set up and maintain. Imagine an organization that has an RBAC matrix using Active Directory users and groups. They would like to manage it on a central security policy server and […]

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Analyzing Data in S3 using Amazon Athena

Neil Mukerje is a Solution Architect for Amazon Web Services Abhishek Sinha is a Senior Product Manager on Amazon Athena Amazon Athena is an interactive query service that makes it easy to analyze data directly from Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to set up or manage and you can […]

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Low-Latency Access on Trillions of Records: FINRA’s Architecture Using Apache HBase on Amazon EMR with Amazon S3

John Hitchingham is Director of Performance Engineering at FINRA The Financial Industry Regulatory Authority (FINRA) is a private sector regulator responsible for analyzing 99% of the equities and 65% of the option activity in the US. In order to look for fraud, market manipulation, insider trading, and abuse, FINRA’s technology group has developed a robust […]

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