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- Title: Big Data Now: Current Perspectives from O'Reilly Radar
- Author(s) O'Reilly Radar Team
- Publisher: OReilly Media August 2011, eBook (2016)
- Permission: This book is provided in digital form with the permission from the rightsholder as part of a Google project to make world's books discoverable online.
- Hardcover/Paperback: N/A
- eBook: 137 pages, in ePub, Mobi, PDF, and Kindle format
- Language: English
- ASIN: B005KDPILI
- ISBN-10: 1-4493-1518-6
- ISBN-13: 978-1-4493-1518-4
- Share This:
This book represents report recaps the trends, tools, applications, and forecasts. This collection of blog posts, authored by leading thinkers and experts in the field, reflects a unique set of themes we've identified as gaining significant attention and traction.
- Careers in data
- Tools and architecture for big data
- Intelligent real-time applications
- Cloud infrastructure
- Machine learning: models and training
- Deep learning and artificial intelligence
- N/A
- Big Data Now: Current Perspectives from O'Reilly Radar (O'Reilly Radar Team)
- The Mirror Site (1) - PDF
- The Mirror Site (2) - PDF
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Engineering Agile Big-Data Systems (Kevin Feeney, et al)
This book outlines an approach to dealing with problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals.
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Knowledge Graphs and Big Data Processing (Valentina Janev, et al)
Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions.
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Big Data in Context: Legal, Social and Technological Insights
This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.
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Modelling and Simulation for Big Data Applications
Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations.
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Disruptive Possibilities: How Big Data Changes Everything
This book takes you on a journey of discovery into the emerging world of big data, from its relatively simple technology to the ways it differs from cloud computing. It provides an historically-informed overview through a wide range of topics.
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The Promise and Peril of Big Data (David Bollier)
This book explores the positive aspects and the social perils that arise when the ever-rising floods of data being generated by mobile networking, cloud computing and other new technologies meets continued innovations in advanced correlation techniques.
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Big Data Processing with Apache Spark (Srini Penchikala)
Learn about the Apache Spark framework and develop Spark programs for use cases in big-data analysis. It covers all the libraries that are part of Spark ecosystem, which includes Spark Core, Spark SQL, Spark Streaming, Spark MLlib, and Spark GraphX.
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The Big Data Agenda: Data Ethics and Critical Data Studies
This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Specific case studies explore how big data have been used in academic work.
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Understanding Big Data: Analytics for Hadoop and Streaming Data
In this book, the three defining characteristics of Big Data - volume, variety, and velocity, are discussed. Industry use cases are also included in this practical guide, to deliver a robust, secure, highly available, enterprise-class Big Data platform.
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O'Reilly® The Data Journalism Handbook (Jonathan Gray, et al.)
This book is intended to be a useful resource for anyone who thinks that they might be interested in becoming a data journalist, or dabbling in Data Dournalism, aims to answer questions like: Where can I find data? How can I request data? etc.
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