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- Title Disruptive Possibilities: How Big Data Changes Everything
- Author(s) Jeffrey Needham
- Publisher: Publisher: O'Reilly Media; eBook (Compliments of Hortonworks)
- Permission: Free eBook Complimented by Hortonworks
- Hardcover/Paperback 94 pages
- eBook HTML
- Language: English
- ISBN-10: 1449369677
- ISBN-13: 978-1449369675
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Big data has more disruptive potential than any information technology developed in the past 40 years. As author Jeffrey Needham points out in this revealing book, big data can provide unprecedented visibility into the operational efficiency of enterprises and agencies.
Disruptive Possibilities provides an historically-informed overview through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds. This relentlessly innovative form of computing will soon become standard practice for organizations of any size attempting to derive insight from the tsunami of data engulfing them.
Replacing legacy silos - whether they're infrastructure, organizational, or vendor silos - with a platform - centric perspective is just one of the big stories of big data. To reap maximum value from the myriad forms of data, organizations and vendors will have to adopt highly collaborative habits and methodologies.
About the Authors- With 25 years experience in both hardware and software engineering, Jeff Needham is a frequent writer and speaker on topics of database performance and scalability, platform engineering and Hadoop cluster technology. Customers appreciate Jeff's creative strategies for evaluating and implementing their big data initiatives.
- Data Analysis and Data Mining
- Big Data
- Data Science
- Statistics, R Language and SAS Programming
- Probability, Stochastic Process, Queueing Theory, etc.
- Books by O'Reilly®
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- Disruptive Possibilities: How Big Data Changes Everything (Jeffrey Needham)
- The Mirror Site (1) - PDF
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The Data Renaissance: Big Data, Artificial Intelligence, and Beyond
This open access book is a comprehensive exploration into the pivotal role of data in shaping our contemporary society. The variety of topics and examples provided on the general topic are a highlight.
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Presents how cutting-edge digital technologies like Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. Also introduces some of the most popular Big Data, AI and Blockchain applications in the sector.
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The Elements of Big Data Value: Research and Ecosystem
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Learning Spark: Lightning-Fast Data Analytics (Jules Damji, et al.)
This book shows data engineers and data scientists why structure and unification in Apache Spark matters. Specifically, it explains how to perform simple and complex data analytics and employ machine learning algorithms.
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Learning Apache Spark with Python (Wenqiang Feng)
This book offers an introduction to the Apache Spark ecosystem, you will learn a wide array of concepts about PySpark in Data Mining, Text Mining, Machine Learning and Deep Learning.
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Trouble With Big Data: Datafication Displaces Cultural Practices
Explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, and the biases and assumptions that drive us.
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Open Source Data Pipelines for Intelligent Applications
Provides data engineers and scientists insight into how Kubernetes provides a platform for building data platforms that increase an organization’s data agility. How Kubernetes has changed the way we process big data and why businesses must adapt.
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