Nouveauté
Big Data Analytics
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- FormatePub
- ISBN8227698230
- EAN9798227698230
- Date de parution25/05/2025
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurBig Dog Books, LLC
Résumé
This comprehensive textbook offers a detailed exploration of Big Data and Hadoop, designed for students, educators, and professionals seeking a strong foundation in modern data processing technologies. Written in clear and accessible English, the book covers the entire Hadoop ecosystem with practical insights, easy-to-understand explanations, and real-world relevance. Beginning with an introduction to digital data types and the evolution of big data, the book progresses through the architecture and design of Hadoop Distributed File System (HDFS), the mechanics of MapReduce, and the functionalities of essential tools like Pig, Hive, HBase, and Big SQL.
The final unit dives into data analytics with R and introduces core machine learning techniques such as supervised and unsupervised learning, making it an ideal reference for applied analytics and intelligent data solutions.
The final unit dives into data analytics with R and introduces core machine learning techniques such as supervised and unsupervised learning, making it an ideal reference for applied analytics and intelligent data solutions.
This comprehensive textbook offers a detailed exploration of Big Data and Hadoop, designed for students, educators, and professionals seeking a strong foundation in modern data processing technologies. Written in clear and accessible English, the book covers the entire Hadoop ecosystem with practical insights, easy-to-understand explanations, and real-world relevance. Beginning with an introduction to digital data types and the evolution of big data, the book progresses through the architecture and design of Hadoop Distributed File System (HDFS), the mechanics of MapReduce, and the functionalities of essential tools like Pig, Hive, HBase, and Big SQL.
The final unit dives into data analytics with R and introduces core machine learning techniques such as supervised and unsupervised learning, making it an ideal reference for applied analytics and intelligent data solutions.
The final unit dives into data analytics with R and introduces core machine learning techniques such as supervised and unsupervised learning, making it an ideal reference for applied analytics and intelligent data solutions.