InfoQ Homepage Data Analysis Content on InfoQ
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Julien Le Dem on the Future of Column-Oriented Data Processing with Apache Arrow
Julien Le Dem, the PMC chair of the Apache Arrow project, presented on Data Eng Conf NY on the future of column-oriented data processing. Apache Arrow is an open-source standard for columnar in-memory execution. InfoQ interviewed Le Dem to find out the differences between Arrow and Parquet.
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Microservices and Stream Processing Architecture at Zalando Using Apache Flink
Javier Lopez and Mihail Vieru spoke at Reactive Summit 2016 Conference about cloud-based data integration and distribution platform used for stream processing in business intelligence use cases. Their solution is based on technologies such as Flink, Kafka and Elasticsearch.
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Stream Processing and Lambda Architecture Challenges
Lambda architecture has been a popular solution that combines batch and stream processing. Kartik Paramasivam at LinkedIn wrote about how his team addressed stream processing and Lambda architecture challenges using Apache Samza for data processing. The challenges described are the late arrival of events and the processing of duplicated messages.
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Reactive Summit 2016 Conference: Reactive Microservices and Staging Data Pipelines
Reactive microservices, data center scale operating system (DCOS), and staging reactive data pipelines were the highlighted topics at Reactive Summit 2016 Conference held this week. InfoQ team attended the conference and this post is a summary of the first day's events at the conference.
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Data Streaming Architecture with Apache Flink
Jamie Grier recently spoke at OSCON 2016 Conference about data streaming architecture using Apache Flink. He talked about the building blocks of data streaming applications and stateful stream processing with code examples of Flink applications and monitoring.
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Precision Medicine Modeling Demonstration with Spark on EMR, ADAM, and the 1000 Genomes Project
AWS engineers Christopher Crosbie and Ujjwal Ratan detail using Spark on EMR for precision medicine data analysis on the ADAM platform with data from the 1000 genomes project.
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Elephant in the Cloud - Hadoop as a Service
Hadoop and other big data technologies revolutionized the way organizations run data analytics but the organizations are still facing challenges with operating costs of using these technologies for on-premise data processing. Ashish Thusoo recently spoke at Enterprise Data World Conference about Hadoop as a service offering that helps organizations bridge the gaps with these capabilities.
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Google Cloud Machine Learning and Tensor Flow Alpha Release
Late last month Google released an alpha version of their TensorFlow (TF) integrated cloud machine learning service as a response to a growing need to make their Tensor Flow library to run at scale on the Google Cloud Platform (GCP). Google describes several new feature sets around making TF usage scale by integrating several pieces of the GCP like Dataproc, a managed Hadoop and Spark service.
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Microsoft Releases Power BI Embedded Preview
Recently at the 2016 Build Event in San Francisco, Microsoft announced a change to their Power BI offering. The update comes in the form of giving customers and ISVs with the ability to embed Power BI reports within their own applications. Microsoft is calling this service Power BI Embedded and it is currently in preview.
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Funnel Analysis at Twitter for Improving User Engagement
Funnel analysis is used to analyze a sequence of events to help with user engagement on a website or a mobile application. Data Science team at Twitter uses this concept to learn how users interact with user interfaces during sign up or tweeting for improving user engagement with Twitter.
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IBM Extends its Cloud Data Analytics Services
IBM has announced four new data services: Analytics Exchange, Compose Enterprise, Graph, and Predictive Analytics. IBM’s new data services are meant to enable users to analyze their own data or get access to datasets provided by IBM. While some of the services run on Bluemix, for others the data can be deployed on other clouds, including private ones.
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How Airbnb Uses Net Promoter Score to Predict Guest Rebooking
Net Promoter Score (NPS) is a customer loyalty metric used to determine the likelihood that a customer will return to a company's website or use their service again. Airbnb uses NPS extensively in measuring the customer loyalty, as a more effective measurement to determine the likelihood that a customer will return to book again or recommend the company to their friends.
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Yahoo! Benchmarks Apache Flink, Spark and Storm
Yahoo! has benchmarked three of the main stream processing frameworks: Apache Flink, Spark and Storm.
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Data Science in F# using FsLab: Interview with Tomas Petricek
FsLab, a collection of F# ooen source libraries for doing Data Science, was released earlier this year, InfoQ reached out with Tomas Petricek, creator of the project, to get more details.
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IBM Brings Watson to IoT
IBM has inaugurated the IoT Global Headquarters and will use the Watson technology to analyze and interpret IoT data.