Book Image

Salesforce Data Architect Certification Guide

By : Aaron Allport
Book Image

Salesforce Data Architect Certification Guide

By: Aaron Allport

Overview of this book

The Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence. The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all the topics necessary to help you pass the exam with ease. You’ll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You’ll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification. By the end of this Salesforce book, you'll have covered everything you need to know to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts.
Table of Contents (23 chapters)
1
Section 1: Salesforce Data Architect Theory
9
Section 2: Salesforce Data Architect Design
15
Section 3: Applying What We've Learned – Practice Questions and Revision Aids

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...