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Salesforce Data Architect Certification Guide

You're reading from   Salesforce Data Architect Certification Guide Comprehensive coverage of the Salesforce Data Architect exam content to help you pass on the first attempt

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781801813556
Length 254 pages
Edition 1st Edition
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Author (1):
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Aaron Allport Aaron Allport
Author Profile Icon Aaron Allport
Aaron Allport
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Table of Contents (23) Chapters Close

Preface 1. Section 1: Salesforce Data Architect Theory
2. Chapter 1: Introducing the Salesforce Data Architect Journey FREE CHAPTER 3. Chapter 2: Data Modeling and Database Design 4. Chapter 3: Master Data Management 5. Chapter 4: Salesforce Data Management 6. Chapter 5: Data Governance 7. Chapter 6: Understanding Large Data Volumes 8. Chapter 7: Data Migration 9. Section 2: Salesforce Data Architect Design
10. Chapter 8: Accounts and Contacts 11. Chapter 9: Data APIs and Apex 12. Chapter 10: Tuning Performance 13. Chapter 11: Backup and Restore 14. Chapter 12: Territory Management 15. Section 3: Applying What We've Learned – Practice Questions and Revision Aids
16. Chapter 13: Practice Exam Questions 17. Chapter 14: Cheat Sheets 18. Chapter 15: Further Resources 19. Chapter 16: How to Take the Exam 20. Chapter 17: Answers to Practice Questions 21. Index 22. Other Books You May Enjoy

Query and search optimization

As we explored in Chapter 6, Understanding Large Data Volumes, consider that Salesforce performs searches in a two-part process. The first part is the creation of a result set that is used to then perform the actual search. Let’s quickly remind ourselves how a result set is produced. When a search is invoked (be it through the Salesforce user interface, a Salesforce API, or Apex code), Salesforce will first search the indexes that have been created for the appropriate records. Taking those results, Salesforce will then apply access permissions, search limits, and any other filters or filter logic to narrow down the results into a result set. That result set is then used to perform an actual search for records in the underlying database.

The way to speed up searches is to think carefully about the indexing of fields that are used when searching in order to speed up the performance of those searches. As seen in Chapter 6, Understanding Large Data...

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