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  • Big Data Processing with Apache Spark - Part 3: Spark Streaming

    In this article, third installment of Apache Spark series, author Srini Penchikala discusses Apache Spark Streaming framework for processing real-time streaming data using a log analytics sample application.

  • 7 Habits of Highly Effective Monitoring Infrastructures

    There is a right way and a wrong way to engineer effective telemetry systems and there is a finite combination of practices which — whatever your choice of individual tools — are predictive of success. If you are building or designing your next monitoring system, take a look at this short list of habits exhibited by the most successful monitoring systems in the world today.

  • The Promise of Healthcare Analytics

    Data analytics play a central role in the healthcare system by improving outcomes and quality of life while helping to control costs. In this article, author describes the role analytics can play with the emerging wearable technologies with biophysical interfaces, physiological sensors, and embedded diagnostic tools.

  • Shaping Big Data Through Constraints Analysis

    In this article, author Carlos Bueno describes a method for analyzing constraints on the shape and flow of data in systems. He talks about the factors useful for system analysis like working set & average transaction sizes, request & update rates, consistency, locality, computation, and latency. He also discusses big data architecture details of two use cases, movie streaming and face recognition.

  • Matt Schumpert on Datameer Smart Execution

    Datameer, a big data analytics application for Hadoop, introduced Datameer 5.0 with Smart Execution to dynamically select the optimal compute framework at each step in the big data analytics process. InfoQ spoke with Matt Schumpert from Datameer team about the new product and how it works to help with big data analytics needs.

  • Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics

    Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics book by Brenda L. Dietrich, Emily C. Plachy, and Maureen F. Norton is a collection of experiences by analytics practitioners in IBM. InfoQ spoke with the authors about the lessons learned from the book, the arsenal of technologies IBM has about Big Data and the future of Analytics.

  • Cindy Walker on Data Management Best Practices and Data Analytics Center of Excellence

    Cindy Walker spoke at Enterprise Data World Conference about using semantic approaches to augment the data management practices. InfoQ spoke with her about the data management best practices and the data analytics center of excellence initiative.

  • Lambda Architecture: Design Simpler, Resilient, Maintainable and Scalable Big Data Solutions

    Lambda Architecture proposes a simpler, elegant paradigm designed to store and process large amounts of data. In this article, author Daniel Jebaraj presents the motivation behind the Lambda Architecture, reviews its structure with the help of a sample Java application.

  • Agility, Big Data, and Analytics

    How do you bringing agility into big data analytics? Learn what makes analytics uniquely different than application development, and how to adapt agile principles and practices to the nuances of analytics. Examine how the disciplines of data science and software development complement one another, and how these intersect in an agile project environment.


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