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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

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781800564893
Length 280 pages
Edition 1st Edition
Languages
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Authors (4):
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Hayley Horn Hayley Horn
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Hayley Horn
Amanda Baker Amanda Baker
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Amanda Baker
Anastasia Prokaieva Anastasia Prokaieva
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Anastasia Prokaieva
Stephanie Rivera Stephanie Rivera
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Stephanie Rivera
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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...

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