Data Lakes and Data Warehouses: Managing Big Data Architectures

EasyChair Preprint no. 10940

Abstract

This research presents a comprehensive exploration of the pivotal role that data storage and management structures play in the world of Big Data. This abstract provides an overview of the book's in-depth analysis and insights. Explore emerging trends and technologies in data management, such as serverless computing, data streaming, and the convergence of data lakes and data warehouses.

In the era of data abundance, organizations are grappling with the challenge of effectively managing and extracting value from vast and diverse datasets. This book delves into the intricacies of data lakes and data warehouses, shedding light on their architecture, implementation, and strategic use in harnessing the potential of Big Data. By immersing themselves in "Data Lakes and Data Warehouses: Managing Big Data Architectures," readers will acquire the knowledge and tools necessary to design, implement, and maintain robust data storage and management solutions for the Big Data era. This book serves as an indispensable guide for data architects, data engineers, IT professionals, and business leaders seeking to harness the full potential of their data assets while ensuring data integrity, accessibility, and analytical capabilities.

Keyphrases: Data Analytic, Data Mining, machine learning

@Booklet{EasyChair:10940,
  author = {Ming Bai and Fatima Tahir},
  title = {Data Lakes and Data Warehouses: Managing Big Data Architectures},
  howpublished = {EasyChair Preprint no. 10940},

  year = {EasyChair, 2023}}