In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Dr. Krishnarajanagar GopalaIyengar Srinivasa is an associate professor and the head of the Department of IT at C.B.P. Government Engineering College, Jaffarpur, New Delhi, India. His other publications include the Springer book Guide to High Performance Distributed Computing. Dr. Gaddadevara Matt Siddesh is an associate professor at the Department of Information Science and Engineering at Ramaiah Institute of Technology, Bangalore, India. Srinidhi Hiriyannaiah is an assistant professor at the Department of Computer Science and Engineering at Ramaiah Institute of Technology, Bangalore, India.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts.Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics. N° de réf. du vendeur 9783319777993
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts.Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics. 424 pp. Englisch. N° de réf. du vendeur 9783319777993
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