Data Processing and Modeling with Hadoop: Mastering Hadoop Ecosystem Including ETL, Data Vault, DMBok, GDPR, and Various Data-Centric Tools (English Edition) Data Processing and Modeling with Hadoop: Mastering Hadoop Ecosystem Including ETL, Data Vault, DMBok, GDPR, and Various Data-Centric Tools (English Edition)

Data Processing and Modeling with Hadoop: Mastering Hadoop Ecosystem Including ETL, Data Vault, DMBok, GDPR, and Various Data-Centric Tools (English Edition‪)‬

    • 8,99 €
    • 8,99 €

Beschreibung des Verlags

Understand data in a simple way using a data lake.

KEY FEATURES  

● In-depth practical demonstration of Hadoop/Yarn concepts with numerous examples.

● Includes graphical illustrations and visual explanations for Hadoop commands and parameters.

● Includes details of dimensional modeling and Data Vault modeling.

● Includes details of how to create and define a structure to a data lake.

DESCRIPTION 

The book 'Data Processing and Modeling with Hadoop' explains how a distributed system works and its benefits in the big data era in a straightforward and clear manner. After reading the book, you will be able to plan and organize projects involving a massive amount of data.

The book describes the standards and technologies that aid in data management and compares them to other technology business standards. The reader receives practical guidance on how to segregate and separate data into zones, as well as how to develop a model that can aid in data evolution. It discusses security and the measures that are utilized to reduce the impact of security. Self-service analytics, Data Lake, Data Vault 2.0, and Data Mesh are discussed in the book.

After reading this book, the reader will have a thorough understanding of how to structure a data lake, as well as the ability to plan, organize, and carry out the implementation of a data-driven business with full governance and security.

WHAT YOU WILL LEARN

● Learn the basics of components to the Hadoop Ecosystem.

● Understand the structure, files, and zones of a Data Lake.

● Learn to implement the security part of the Hadoop Ecosystem.

● Learn to work with the Data Vault 2.0 modeling.

● Learn to develop a strategy to define good governance.

● Learn new tools to work with Data and Big Data

WHO THIS BOOK IS FOR  

This book caters to big data developers, technical specialists, consultants, and students who want to build good proficiency in big data. Knowing basic SQL concepts, modeling, and development would be good, although not mandatory.

AUTHOR BIO 

Vinicius Aquino do Vale is an experienced technical consultant who has been working with clients and partners for 15 years in the design of technological solutions. In his career, Vinicius has participated in large projects as a specialist in Big Data technologies, having advanced knowledge of the Hadoop ecosystem. He has worked on several Big Data projects in the largest companies in Brazil assisting in architecture design, implementation, configuration, ingestion, analysis and ETL. He participated in the construction of all data lake / smart data flows, in addition to integrating the entire system with analytics tools like QLikSense, QlikView, Tableau, Metabase, Tibco SpotFire, in addition to implementing security integration with AD / LDAP.

GENRE
Computer und Internet
ERSCHIENEN
2021
12. Oktober
SPRACHE
EN
Englisch
UMFANG
196
Seiten
VERLAG
BPB Publications
GRÖSSE
3,6
 MB

Mehr ähnliche Bücher

Handbook of Data Management 1999 Edition Handbook of Data Management 1999 Edition
2021
Information Governance Principles and Practices for a Big Data Landscape Information Governance Principles and Practices for a Big Data Landscape
2014
Simplifying Data Engineering and Analytics with Delta Simplifying Data Engineering and Analytics with Delta
2022
Architecting Data-Intensive Applications Architecting Data-Intensive Applications
2018
IBM Information Server: Integration and Governance for Emerging Data Warehouse Demands IBM Information Server: Integration and Governance for Emerging Data Warehouse Demands
2013
Building Big Data and Analytics Solutions in the Cloud Building Big Data and Analytics Solutions in the Cloud
2014