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

Enterprise data governance

Every organization, whether small or large, collects data, usually from multiple sources, and is responsible for ensuring that processes are in place to handle data in a consistent manner. It must do that in such a way that is compliant with data-related regulations and laws that the organization is subject to.

Organizations also make decisions about data, for example, where to store data, who can access it, and how long to keep it, but some organizations consciously put in the effort and formalize this decision-making process while others may not do so. Those that do this in a formal manner realize more value over a period of time while also minimizing their exposure to the risk caused by informal data governance processes.

In the next few sections, we will start by defining data governance, clearly articulating the business drivers behind it, the benefits of formal data governance, and other related aspects of data governance.

What is data governance...