knowledge discovery using big di agarwal ruchi (5 risultati)

Taschenbuch. Condizione: Neu. Neuware -In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).Books on Demand GmbH, Überseering 33, 22297 Hamburg 84 pp. Englisch.

Paperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Agarwal RuchiThe Authors of this book have been actively involved in the research field of Big Data Analytics. They have published various books and papers in international refereed journals and prestigious conferences. Presently, th.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS). 84 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the present scenario, Hadoop is just like the kernel for big data, having distributed storage and compute capabilities to handle structured/semi-structured/unstructured data. Hadoop framework is also utilized for data warehousing and in the field of data science, which makes new informative discoveries about data. In this book two advanced algorithm named as K-Means Clustering and Frequent Item sets mining are applied on Hadoop MapReduce environment, which presents them in a problem/solution format. Predictive analysis of the output is done with the help of Tableau. Each problem is explored step by step, which automatically helps the reader in growing more comfortable with Hadoop in the world of big data. This hand book helps the reader to demonstrate how the real world data is handled using hadoop framework. It also helps readers in understanding the basic concepts of MapReduce and Hadoop Distributed File System (HDFS).