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

A day in the life of a data architect

In this section, we will explore a day in a data architect's life. As we stated in the introduction, this can help us understand and put into context some of the things that data architects do. It also helps us to translate their responsibilities in a practical way. Keep in mind that this is provided just as a general idea of how data architects spend their day and shouldn't be taken as an exact sequence of how they go about completing their duties:

The morning may look as follows:

  • Document the proposed data model for an enhancement project related to order fulfillment. Prepare a presentation for the enterprise, IS, and integration architects and other technical stakeholders.
  • Participate in a weekly meeting with EAs and other domain architects to align on existing policies and guidelines and new ones that may be under consideration.
  • Participate in a project meeting with an integration architect and a System, Applications, and Products (SAP) solution architect looking to integrate work orders and invoicing with SAP and Salesforce.

The afternoon may look as follows:

  • Analyze requirements from operations requiring access to Opportunity and Opportunity Products data in a data warehouse for reporting. Opportunity data is more than 5 million rows.
  • Work on a request to archive Opportunity and Opportunity Products data. Look into the pros and cons of using big objects, Heroku, or other available options.
  • Understand the capabilities of Einstein Analytics and explore its use cases and how it could meet the organization's analytics requirements. Also, explore Salesforce Tableau and its capabilities for reporting needs that are challenging to meet using the native reports and dashboards functionality.
  • Present the proposed data model for the order fulfillment project. Field questions and seek feedback from the team.

In this section, we looked at a data architect's day to gain a better understanding of the role, the interactions they have with other stakeholders in the organization, and a glimpse of the research and prototyping that is required to be successful in the role.