Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Databricks ML in Action

You're reading from   Databricks ML in Action Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment

Arrow left icon
Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781800564893
Length 280 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (4):
Arrow left icon
Hayley Horn Hayley Horn
Author Profile Icon Hayley Horn
Hayley Horn
Amanda Baker Amanda Baker
Author Profile Icon Amanda Baker
Amanda Baker
Anastasia Prokaieva Anastasia Prokaieva
Author Profile Icon Anastasia Prokaieva
Anastasia Prokaieva
Stephanie Rivera Stephanie Rivera
Author Profile Icon Stephanie Rivera
Stephanie Rivera
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Part 1: Overview of the Databricks Unified Data Intelligence Platform FREE CHAPTER
2. Chapter 1: Getting Started and Lakehouse Concepts 3. Chapter 2: Designing Databricks: Day One 4. Chapter 3: Building the Bronze Layer 5. Part 2: Heavily Project Focused
6. Chapter 4: Getting to Know Your Data 7. Chapter 5: Feature Engineering on Databricks 8. Chapter 6: Tools for Model Training and Experimenting 9. Chapter 7: Productionizing ML on Databricks 10. Chapter 8: Monitoring, Evaluating, and More 11. Index 12. Other Books You May Enjoy

Planning your platform

This section covers topics for discussion before and during the DI Platform setup process. The role of the data team often determines the platform setup. One of Databricks’ ideal attributes is that the technology stack is unified, making the setup and collaboration between teams more straightforward. The data team reporting structure frequently determines the border where one role ends and another begins, rather than the actual data product workflow. Luckily, we do not have to worry because the DI Platform serves data engineers, scientists, and analysts alike.

In Figure 2.1, you can see an end-to-end lakehouse architecture and the components in Databricks.

Figure 2.1 – Overview of a lakehouse architecture and how Databricks DI Platform fits this paradigm

Figure 2.1 – Overview of a lakehouse architecture and how Databricks DI Platform fits this paradigm

The DI Platform consists of one or more Databricks accounts. Most of the time, companies only have one. However, there are situations where companies require extra...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime