"Die Big-Data-Odyssee: Einblicke, Innovationen und Auswirkungen gewinnen" ist ein umfassender Leitfaden zu Big Data und Hadoop. Das Buch beginnt mit einer Einführung in Big Data, seine Quellen, Geschichte, Antriebskräfte, Merkmale und Anwendungen. Anschließend werden die wichtigsten Merkmale wie intelligente Datenanalyse, die Art der Daten, Analyseprozesse, Tools, Sicherheit, Compliance, Auditing, Schutz, Privatsphäre und Ethik behandelt. Als Nächstes wird auf Hadoop eingegangen, einschließlich seiner Geschichte, des Apache Hadoop-Projekts, des Hadoop Distributed File System (HDFS), des...

"The Big Data Odyssey: Navigating Insights, Innovation, and Impact" is a comprehensive guide to big data and Hadoop, this book starts by introducing big data, its sources, history, drivers, characteristics, and applications. It then delves into key features like intelligent data analysis, data nature, analytic processes, tools, security, compliance, auditing, protection, privacy, and ethics. Next, it explores Hadoop, including its history, the Apache Hadoop project, Hadoop Distributed File System (HDFS), the Hadoop ecosystem, data formats, data analysis, scaling, streaming, and pipes. Moving...

"L'odyssée du Big Data : Naviguer vers la connaissance, l'innovation et l'impact" est un guide complet sur les big data et Hadoop. Ce livre commence par présenter les big data, leurs sources, leur histoire, leurs moteurs, leurs caractéristiques et leurs applications. Il se penche ensuite sur des éléments clés tels que l'analyse intelligente des données, la nature des données, les processus analytiques, les outils, la sécurité, la conformité, l'audit, la protection, la confidentialité et l'éthique. Il explore ensuite Hadoop, notamment son histoire, le projet Apache Hadoop, le...

Dive into the world of big data with the comprehensive guide 'Hadoop Ecosystem, YARN, NoSQL, MongoDB, Spark & Scala Guide.' In Chapter 1, explore the intricacies of the Hadoop ecosystem and YARN, covering components, HDFS, MapReduce, YARN, PIG, HIVE, schedulers, failover, fencing, and HDFS federation. Chapter 2 introduces NoSQL databases, providing insights into different types, including document databases, key-value stores, column-oriented databases, and graph databases. Chapter 3 delves into MongoDB, offering an in-depth understanding of its introduction, data types, document creation,...

This book "Foundations of Big Data Processing: A Comprehensive Guide to Pig, Hive, and HBase" as it navigates through pivotal frameworks. Chapter 1 introduces Pig, its applications, and comparisons with databases, detailing Grunt, Pig Latin, and essential elements. Chapter 2 delves into statements, control flow, types, null values, and user-defined functions. Chapter 3 covers Java-based UDFs. Chapter 4 focuses on Hive, encompassing architecture, services, installation, HiveQL, data types, tables, and advanced topics like joins and subqueries. Chapter 5 explores HBase, including concepts,...