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

Revisiting databases

Before we dive deep into LDVs and some associated topics, let's take a brief history trip. Understanding relational and non-relational databases will help us understand the different types of solutions that are available with Salesforce and assist us in determining which one to use depending on requirements. In the early days of modern computing, tapes were used for storage, and the first digital-tape storage system, IBM's Model 726, could store 1.1 MB (megabytes) on a single reel of data. For comparison purposes, these days, a tape cartridge can hold up to 15 terabytes (TB). Model 726 was a non-relational database in that it was free-form records linked together.

Then came relational databases, which offered a more organized approach to store, retrieve, and search data. Data was stored in multiple tables in keeping with normalization principles and logically linked together using unique identifiers called primary and foreign keys. Refer to Chapter...