Unisciti a noi in un viaggio nel mondo dei libri!
Aggiungi questo libro allo scaffale
Grey
Scrivi un nuovo commento Default profile 50px
Grey
Ascolta online i primi capitoli di questo audiolibro!
All characters reduced
Mastering Data-Intensive Applications - Building for Scale Speed and Resilience - cover
RIPRODURRE CAMPIONE

Mastering Data-Intensive Applications - Building for Scale Speed and Resilience

Chuck Sherman

Narratore Ray Collins

Casa editrice: Chuck Sherman

  • 0
  • 0
  • 0

Sinossi

In an era dominated by data, the ability to harness its power is a game-changer for businesses and industries. "Mastering Data-Intensive Applications" is your definitive guide to navigating the complex landscape of building and managing applications that can handle the massive volumes of data that define the modern world. 
This book delves into the core principles, strategies, and best practices required to architect, develop, and maintain data-intensive applications that excel in scale, speed, and resilience. Whether you're a seasoned software engineer, a system architect, or a technical leader, this book will empower you to conquer the challenges of working with data at an unprecedented scale. 
"Mastering Data-Intensive Applications" is more than just a technical manual—it's a comprehensive journey through the intricacies of modern application development. Authored by experts in the field, this book combines theoretical knowledge with practical wisdom, enabling you to create applications that are not only responsive and robust but also capable of extracting valuable insights from the vast sea of data. 
Equip yourself with the skills to architect data-intensive applications that excel in scale, speed, and resilience. Whether you're building the next social media sensation, revolutionizing e-commerce, or driving advancements in healthcare analytics, this book will be your steadfast companion in the world of data-intensive application mastery. 
 
Durata: circa 4 ore (03:57:32)
Data di pubblicazione: 05/12/2024; Unabridged; Copyright Year: — Copyright Statment: —