Escucha y lee

Descubre un mundo infinito de historias

  • Lee y escucha todo lo que quieras
  • Más de 900 000 títulos
  • Títulos exclusivos + Storytel Originals
  • 7 días de prueba gratis, luego $7.99 /mes
  • Cancela cuando quieras
Suscríbete ahora
Copy of Device Banner Block 894x1036 3

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

3 Calificaciones

4.3

Duración
17H 31min
Idioma
Inglés
Format
Categoría

No ficción

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology.

This book will help you: get a concise overview of the entire data engineering landscape; assess data engineering problems using an end-to-end framework of best practices; cut through marketing hype when choosing data technologies, architecture, and processes; use the data engineering lifecycle to design and build a robust architecture; and incorporate data governance and security across the data engineering lifecycle.

© 2023 Ascent Audio (Audiolibro): 9781663732347

Fecha de lanzamiento

Audiolibro: 21 de noviembre de 2023

Otros también disfrutaron...

  1. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Martin Kleppmann
  2. Data Science for Beginners: Comprehensive Guide to Most Important Basics in Data Science Alex Campbell
  3. AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence Laurence Moroney
  4. Data Science John D. Kelleher
  5. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking Foster Provost
  6. Data as a Product: How to Provide the Data That the Company Needs Brian Murray
  7. Data Mesh: What Is Data Mesh? Principles of Data Mesh Architecture Brian Murray
  8. Data Mesh: Comprehensive Guide on How to Become Truly Data-Driven Alex Campbell
  9. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are Seth Stephens-Davidowitz
  10. Data Smart: Using Data Science to Transform Information into Insight John W. Foreman
  11. AI and Machine Learning for On-Device Development: A Programmer's Guide, 1st Edition Laurence Moroney
  12. Data Engineering: Analyzing Big Data and Modern Data Phil Gilberts
  13. Data Management Introbooks Team
  14. Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses Michele Chambers
  15. Learning from Data Introbooks Team
  16. Learning Systems Thinking: Essential Non-Linear Skills and Practices for Software Professionals Diana Montalion
  17. Data Quality Prashanth Southekal
  18. Computational Thinking Peter J. Denning
  19. Ultimate Data Engineering with Databricks Mayank Malhotra
  20. Database Internals: A Deep Dive into How Distributed Data Systems Work, 1st Edition Alex Petrov
  21. The Kaggle Book: Data analysis and machine learning for competitive data science Luca Massaron
  22. 97 Principles for Software Architects: Axioms for software architecture and development written by industry practitioners Multiple Authors
  23. Learning SQL: Generate, Manipulate, and Retrieve Data, 3rd Edition Alan Beaulieu
  24. Fundamentals of Software Architecture: An Engineering Approach Neal Ford
  25. Coders: Who They Are, What They Think and How They Are Changing Our World Clive Thompson
  26. The Clean Coder: A Code of Conduct for Professional Programmers Robert C. Martin
  27. Data Mesh: Delivering Data-Driven Value at Scale Zhamak Dehghani
  28. Coders at Work: Reflections on the Craft of Programming Peter Seibel
  29. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World Karim R. Lakhani
  30. Building Microservices: Designing Fine-Grained Systems Sam Newman
  31. The Deep Learning Revolution Terrence J. Sejnowski
  32. Docker Essentials: Simplifying containerization : A Beginner's Guide Mike Wilson
  33. The Creativity Code: How AI is learning to write, paint and think Marcus du Sautoy
  34. AI at the Edge: Solving Real-World Problems with Embedded Machine Learning Jenny Plunkett
  35. Google Cloud Cookbook: Practical Solutions for Building and Deploying Cloud Services, 1st Edition Rui Costa
  36. Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith Sam Newman
  37. How Smart Machines Think Sean Gerrish
  38. Machine Learning Interviews: Kickstart Your Machine Learning and Data Career Susan Shu Chang
  39. The AI Delusion Gary Smith
  40. AI Engineering: Building Applications with Foundation Models Chip Huyen
  41. Business Intelligence For Dummies Swain Scheps
  42. Deep Learning John D. Kelleher
  43. The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity Byron Reese
  44. Software Engineering at Google: Lessons Learned from Programming Over Time Tom Manshreck

Siempre con Storytel:

  • Acceso ilimitado

  • Modo sin conexión

  • Modo Infantil

  • Cancela en cualquier momento

Historias ilimitadas siempre
Oferta por tiempo limitado

Ilimitado

Para los que quieren escuchar y leer sin límites.

$7.99 /mes
  • 1 cuenta

  • Acceso ilimitado

  • Escucha y lee los títulos que quieras

  • Modo sin conexión + Modo Infantil

  • Cancela en cualquier momento

Pruébalo ahora