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

Loading high-quality data

When users interact with data, the data must be of good quality for it to be effective. For example, salespeople may go to look at a Contact record in Salesforce to make a call to try and up-sell or cross-sell to that customer. If users are presented with multiple Contact records for the same person (duplicates), and those records are at different levels of completeness, they may end up very annoyed. Due to this, those users may not have all of the information for a Contact or, worse, are still jumping between records to deduce the correct phone number to call or email address to use.

As mentioned previously, practical steps can be taken as part of a data migration process. When preparing data before loading it, or once the data has been loaded into the target system, cleansing, de-duplication, and (optionally) enrichment must take place. When thinking about the quantity of data as well as its quality, it may make sense for some enterprises to perform the...