InfoQ Homepage Real-Time Data Content on InfoQ
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Real-Time Data Analysis and ML for Fraud Prevention
Mikhail Kourjanski addresses the architectural approach towards the PayPal internally built real-time service platform, which delivers performance and quality of decisions.
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Real-Time Data Activation - Analytics, Intelligence & Decision Making
Marcelo Wiermann discusses dealing with real-time analytics with the Lambda Architecture, creating a working data set and data-driven features in an application.
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Extreme Programming Meets Real-time Data
Tom Johnson and Gel Goldsby talk about scaling problems they encountered at Unruly, and where extreme programming values led them.
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Exploring Wikipedia with Apache Spark: A Live Coding Demo
Sameer Farooqui demos connecting to the live stream of Wikipedia edits, building a dashboard showing what’s happening with Wikipedia datasets and how people are using them in real time.
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Real-time Stream Computing & Analytics @Uber
Sudhir Tonse discusses using stream processing at Uber: indexing and querying of geospatial data, aggregation and computing of streaming data, extracting patterns, TimeSeries analyses and predictions.
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Developing Real-time Data Pipelines with Apache Kafka
Joe Stein makes an introduction for developers about why and how to use Apache Kafka. Apache Kafka is a publish-subscribe messaging system rethought of as a distributed commit log.
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Pulsar: Real-time Analytics at Scale
Sharad Murthy & Tony Ng present Pulsar, a real-time streaming system which can scale to millions of events per second with high availability and 4GL language support.
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Machine Learning and IoT
Ajit Jaokar discusses data science and IoT: sensor data, real-time processing, cognitive computing, integration of IoT analytics with hardware, IoT’s impact on healthcare, automotive, wearables, etc.
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How 30 Years of Ticket Transaction Data Helps you Discover New Shows!
Vaclav Petricek discusses how to train models, architect and build a scalable system powered by Storm, Hadoop, Spark, Spring Boot and Vowpal Wabbit that meets SLAs measured in tens of milliseconds.
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Java 8 in Anger
Trisha Gee uses Java 8 streams and lambdas to build an app consuming a real-time feed of high velocity data, using services to make sense of the data, and presenting it in a JavaFX dashboard.
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IoT Realized - The Connected Car
This session explores the power of Spring XD in the context of the Internet of Things (IoT).
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Better Together - Using Spark and Redshift to Combine Your Data with Public Datasets
Eugene Mandel discusses challenges of conforming data sources and compares processing stacks: Hadoop+Redshift vs Spark, showing how the technology drives the way the problem is modeled.
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