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)
1
Section 1: Data Architecture and Data Management Essentials
5
Section 2: Salesforce Data Governance and Master Data Management
9
Section 3: Large Data Volumes (LDVs) and Data Migrations

Assessing the current state of data governance

We have discussed data governance and how it's different from data management and the ways to implement data governance policies with respect to Salesforce. But before we start to implement data governance policies and tools, it's recommended to do a current state assessment. The reason is that every organization has some form of data governance in place and there is no need to scrap these practices. Rather, we need to understand what these are and identify the gaps. After we validate and realize that the existing policies are adequate, we can turn our attention to these gaps and ensure they are taken care of.

In the following sections, we will discuss what a data governance assessment is, some of the challenges that we may face in an assessment, and high-level steps on how to go about doing it.

Assessing the current landscape

The goal behind a data governance assessment is to document the knowledge, skills, and attitude...