Book Image

Salesforce Data Architecture and Management

By : Ahsan Zafar
Book Image

Salesforce Data Architecture and Management

By: Ahsan Zafar

Overview of this book

As Salesforce orgs mature over time, data management and integrations are becoming more challenging than ever. Salesforce Data Architecture and Management follows a hands-on approach to managing data and tracking the performance of your Salesforce org. You’ll start by understanding the role and skills required to become a successful data architect. The book focuses on data modeling concepts, how to apply them in Salesforce, and how they relate to objects and fields in Salesforce. You’ll learn the intricacies of managing data in Salesforce, starting from understanding why Salesforce has chosen to optimize for read rather than write operations. After developing a solid foundation, you’ll explore examples and best practices for managing your data. You’ll understand how to manage your master data and discover what the Golden Record is and why it is important for organizations. Next, you'll learn how to align your MDM and CRM strategy with a discussion on Salesforce’s Customer 360 and its key components. You’ll also cover data governance, its multiple facets, and how GDPR compliance can be achieved with Salesforce. Finally, you'll discover Large Data Volumes (LDVs) and best practices for migrating data using APIs. By the end of this book, you’ll be well-versed with data management, data backup, storage, and archiving in Salesforce.
Table of Contents (14 chapters)
Section 1: Data Architecture and Data Management Essentials
Section 2: Salesforce Data Governance and Master Data Management
Section 3: Large Data Volumes (LDVs) and Data Migrations


We started off by discussing the types of databases to give an overview of what is out there. We all know that the Salesforce platform is largely built on relational databases, more specifically, Oracle databases, but not everything in the Salesforce ecosystem is hosted on a relational database.

The discussion around determining whether you are in an LDV scenario will hopefully prompt you next time when you are in a similar situation to thoroughly assess the factors that can contribute to LDV scenarios even if the rough threshold of a million records is not met. In addition to that, the considerations for LDVs are not only important for LDV scenarios, but some of the discussion is relevant to general data migration and integration as well. I know that the Preventing LDV scenarios section has a provocative title, but the thought behind it is that there are ways to prevent an LDV scenario, again acknowledging the fact that it may not be possible when you have 5 million Account...