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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

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781801073240
Length 376 pages
Edition 1st Edition
Concepts
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Author (1):
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Ahsan Zafar Ahsan Zafar
Author Profile Icon Ahsan Zafar
Ahsan Zafar
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Table of Contents (14) Chapters Close

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

The Execution phase

This is the phase where the rubber meets the road and all the work done in the previous phase gets tested. By this phase, you will have achieved a good understanding of the scope, the type of data, assumptions, and constraints you are dealing with. Let's discuss the best practices that can be applied in this phase.

Best practices

Your mapping document is ready and the tool that you will use along with any staging databases are all set and ready for that moment of truth. You are eager to click the Run button and see how the first dry run with some preliminary data goes. To be clear, the execution phase here refers to running your data loads in a sandbox environment and is not limited to production runs. We will discuss specific production environment runs in a later section. Here are some best practices that will increase your chances of success with this phase:

  • Start small: Start with small loads and iron out any issues before trying large loads...
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