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

Chapter 7: Working with Large Volumes of Data

In this chapter, we will discuss working with big data in Salesforce. Salesforce has been in use by organizations for a long time, and more and more organizations have moved from the implementation and stabilization phase to a more mature growth stage where the focus is on leveraging features introduced during the implementation phase to increase revenues and reduce costs. Business growth means data is growing as well and it needs to be managed properly to prevent any disruption to the business.

We will take a brief dip into different types of databases and then dive right into Large Data Volumes (LDVs), a topic that piques my interest because of the unique challenges associated with it. We will look at what defines an LDV scenario and also discuss how we can avoid these scenarios when possible. And when we do find ourselves working with LDVs, we'll see some of the considerations to take into account to be successful along with...