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

Salesforce Platform performance

Over time, data in your organization will grow. If this growing data is not managed properly, it can cause issues, including performance issues, storage limits, and low adaption of the system. One of the best ways to manage data over the long run is to incorporate data archiving and data management practices as part of every new implementation. When this is not done, data archiving and stewardship activities become afterthoughts and require more work to implement. This is regardless of factors including having sufficient storage for the next few years, good performance, a lack of performance-related complaints from customers, or thinking that you will never hit the limits.

Good architecture means thinking ahead about performance and minimizing, where it makes sense, the use of available resources. In this section, we will review why performance matters and some of the more common reasons that cause performance issues. We will also be reviewing performance...