Introducing the learning journey

Throughout this book, the certification learning journey will be broken down into the theory and the designer parts of the exam. The theory will align closely with the curriculum that's described in the exam guide, with the designer section dedicated to learning about the practical concepts referenced in the theory – for example, learning about Person Accounts and how they affect the data model and sharing thereof.

The learning journey starts with the theoretical concepts behind the exam:

• Data Modeling and Database Design:
  • Understanding how the Salesforce data model is architected, the design decisions behind that, and how the model affects sharing and security.
  • Understanding the different types of objects and how these fit into the data model design strategy.
  • Understanding data skew, which will provide you with an understanding of this concept in Salesforce.
• Master Data Management:
  • Understanding how to effectively design and implement a Master Data Management (MDM) strategy on the Salesforce platform.
  • Being able to articulate the concept of a golden record, preserve data traceability across multiple data sources, and understand how this affects the context that business rules run in.
• Salesforce Data Management:
  • How Salesforce license types affect the data model and the sharing options available to work with. Understanding these, as well as how to govern the data on the platform, is crucial to designing scalable, performant solutions that combine data from one or more Salesforce instances.
• Data Governance:
  • Being able to safeguard data on the Salesforce platform is a key part of the Salesforce Data Architect's role. This chapter covers the concepts behind building compliant solutions and how the Salesforce platform can underpin an enterprise data governance strategy.
• Large Data Volumes:
  • Whilst the Salesforce platform can cope with large amounts of data, some considerations apply to larger/massive amounts of data (referred to as large data volumes) and how the performance on the platform is affected.
  • This chapter covers LDV considerations and mitigations, as well as scalable data model design and data archiving strategies.
• Data Migration:
  • How do you get good quality data into the Salesforce platform?
  • How do you ensure loading large amounts of data is smooth, reliable, repeatable, and timely?
  • How do you effectively export data from the Salesforce platform?

Next, we'll look at the designer concepts that apply practical knowledge and practices to hone the theory:

• Accounts and Contacts:
  • We will cover the Account/Contact model, including Person Accounts and Contacts to Multiple Accounts, account skew, and the implications this has on the performance of queries and reports.
• Data APIs and Apex:
  • We will understand the various Lightning Platform APIs and Apex operations (including database, batch, and asynchronous), and how to deploy them effectively when designing data operations on the Salesforce Customer 360 Platform.
• Tuning Performance:
  • We will learn about the various methods that are available for tuning performance when designing Salesforce applications on the Salesforce Customer 360 Platform.
• Backup and Restore:
  • We will understand the methods that are available for getting data out of and back into the Salesforce platform while focusing on data backup and restore. This is useful when you're designing ETL and other solutions as part of an overall Salesforce IT estate.
• Territory Management:
  • We will understand territory management and how it pertains to the data model and its usage design on the Salesforce Lightning Platform.

Lastly, there is a section of this book that's dedicated to exam success that focuses on the following:

• Practice questions and answers
• Cheatsheets
• Introduction to further reading on some of the concepts and topics mentioned in this book
• An overview of Webassessor, including how to sign up for and take the exam