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Salesforce Data Architecture and Management

You're reading from Salesforce Data Architecture and Management A pragmatic guide for aspiring Salesforce architects and developers to manage, govern, and secure their data effectively

Product type Paperback

Published in Jul 2021

Publisher Packt

ISBN-13 9781801073240

Length 376 pages

Edition 1st Edition

Tools

Salesforce

Concepts

CRM

Author (1):

Ahsan Zafar

View More author details

Table of Contents (14) Chapters

Preface

1. Section 1: Data Architecture and Data Management Essentials

2. Chapter 1:Data Architect Roles and Responsibilities FREE CHAPTER

3. Chapter 2: Understanding Salesforce Objects and Data Modeling

4. Chapter 3: Understanding Data Management

5. Section 2: Salesforce Data Governance and Master Data Management

6. Chapter 4: Making Sense of Master Data Management

7. Chapter 5: Implementing Data Governance

8. Chapter 6: Managing Performance

9. Section 3: Large Data Volumes (LDVs) and Data Migrations

10. Chapter 7: Working with Large Volumes of Data

11. Chapter 8: Best Practices for General Data Migration

12. Assessments

13. Other Books You May Enjoy

Section 1: Data Architecture and Data Management Essentials

By the end of this section, you will have understood the role of a data architect and the skills that are required to be successful in the role. You will understand what data modeling is, how to apply data modeling concepts in Salesforce, and how they relate to objects and fields in Salesforce. Concepts related to data management and the different aspects of data management will be discussed. Backup and archiving strategies and some tools to use to manage data will also be discussed with hands-on exercises.

In this section, there are the following chapters:

Chapter 1, Data Architect – Roles and Responsibilities
Chapter 2, Understanding Salesforce Objects and Data Modeling
Chapter 3, Understanding Data Management

The rest of the chapter is locked

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Authors (1)

Zafar

Zafar

Iffat Zafar was born in Pakistan. She received her Ph.D. from the Loughborough University in Computer Vision and Machine Learning in 2008. After her Ph.D. in 2008, she worked as research associate at the Department of Computer Science, Loughborough University, for about 4 years. She currently works in the industry as an AI engineer, researching and developing algorithms using Machine Learning and Deep Learning for object detection and general Deep Learning tasks for edge and cloud-based applications.

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