InfoQ Homepage Big Data Content on InfoQ
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Machine Learning and Cognitive Computing
Based on a webinar on analytics, this article covers the topics of machine learning and cognitive computing, and how these fields are related to artificial intelligence (AI). Panelists discuss how this technology is being applied in digital marketing space and what concerns organizations have in providing machine learning services.
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Garage Door Openers: An Internet of Things Case Study
In this article, author discusses how to design an Internet-connected garage door opener ("IoT opener") to be secure. He talks about cloud service authentication and security improvements offered by networked openers, like two-factor authentication (2FA). He also discusses security infrastructure for IoT devices, which includes user authentication, access policy creation & enforcement.
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Big Data as a Service, an Interview with Google's William Vambenepe
Many of the Big Data technologies in common use originated from Google and have become popular open source platforms, but now Google is bringing an increasing range of big data services to market as part of its Google Cloud Platform. InfoQ caught up with Google's William Vambenepe, who's lead product manager for Big Data services to ask him about the shift towards service based consumption.
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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.
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Big Data and IT-Enabled Services: Ecosystem and Coevolution?
In this article, based on a research study, author presents big data as a service-oriented and evolutionary case of disruptive IT-enabled services (IESs) rather than as datasets. Big data services emerge from combining diverse resources from an ecosystem of technologies, market needs, social actors, and other institutional contexts.
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Analytics, Machine Learning, and the Internet of Things
In this article, author discusses the evolving technologies like Machine Learning and Internet of Things and how to exploit them for data analytics. He also talks about how organizations can benefit from these new sources of information and intelligence embedded in their environments.
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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.
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Big Data Processing with Apache Spark - Part 2: Spark SQL
Spark SQL, part of Apache Spark big data framework, is used for structured data processing and allows running SQL like queries on Spark data. In this article, Srini Penchikala discusses Spark SQL module and how it simplifies running data analytics using SQL interface. He also talks about the new features in Spark SQL, like DataFrames and JDBC data sources.
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Highly Distributed Computations Without Synchronization
Synchronization of data across systems is expensive and impractical when running systems at scale. Traditional approaches for performing computations or information dissemination are not viable. In this article Basho Sr. Software Engineer Chris Meiklejohn explores the basic building blocks for crafting deterministic applications that guarantee convergence of data without synchronization.
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Big Data Processing with Apache Spark – Part 1: Introduction
Apache Spark is an open source big data processing framework built around speed, ease of use, and sophisticated analytics. In this article, Srini Penchikala talks about how Apache Spark framework helps with big data processing and analytics with its standard API. He also discusses how Spark compares with traditional MapReduce implementation like Apache Hadoop.
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Apache Ignite GridGain Incubator Project - Q&A Interview with Nikita Ivanov
GridGain announced that the In-Memory Data Fabric has been accepted into Apache Incubator program as Apache Ignite. InfoQ spoke with Nikita Ivanov about their product becoming part of Apache.
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Interview with Alex Holmes, author of “Hadoop in Practice. Second Edition”
The new “Hadoop in Practice. Second Edition” book by Alex Holmes provides a deep insight into Hadoop ecosystem covering a wide spectrum of topics such as data organization, layouts and serialization, data processing, including MapReduce and big data patterns, special structures along with their usage to simplify big data processing, and SQL on Hadoop data.