Salesforce Data Architect Certification Guide E-Book

Aaron Allport

• Herausgeber: Packt Publishing
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 319

Veröffentlichungsjahr: 2022

Beschreibung

The Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence.
The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all the topics necessary to help you pass the exam with ease. You’ll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You’ll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification.
By the end of this Salesforce book, you'll have covered everything you need to know to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts.

Leseprobe

Salesforce Data Architect Certification Guide

Comprehensive coverage of the Salesforce Data Architect exam content to help you pass on the first attempt

Aaron Allport

BIRMINGHAM—MUMBAI

Salesforce Data Architect Certification Guide

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Contributors

About the author

Aaron Allport is a Salesforce architect and has worked with CRM systems and integrations for his entire professional career. Aaron specializes in Salesforce technical architecture and integration, helping his clients ensure they get the most from their technology investment. Aaron has spoken at Dreamforce, written about everything from DevOps to data architecture online, and can regularly be found at the Salesforce London developer meetup.

To my mother, Deborah – you taught me that anything is possible.

To Steph, Isla, Noah, and Theo. You’re my world. This book wouldn’t be possible without your love, encouragement, and support.

About the reviewer

Rajvardhan Oak is a cyber security researcher who is passionate about making the internet a safer place for everyone. His research interests are cyber security, privacy, and their intersection with machine learning. He currently works as an applied scientist at Microsoft. As part of the ad fraud detection team, his work involves analyzing network traffic and building models to filter click fraud. He is also pursuing a Ph.D. at the University of California Davis, where his research examines the underground ecosystems of reputation manipulation via fraudulent reviews. He also has extensive experience in programming and a strong command over data governance, privacy-preserving analytics, and threat modeling, as well as other security areas.

Table of Contents

Preface

Section 1: Salesforce Data Architect Theory

1

Introducing the Salesforce Data Architect Journey

What is the Data Architecture and Management credential?

Introducing the exam

Playground environments

Documenting designs and design decisions

Other Salesforce credentials in the Application Architect domain

Profile of a Salesforce Data Architect

Introducing the learning journey

Summary

Practice questions

Further reading

2

Data Modeling and Database Design

The Salesforce data model

Understanding Salesforce sharing and security

Organization-Wide Defaults

Profiles and permission sets

Role Hierarchy

Sharing rules

Manual sharing

Team access

Territory hierarchy access

Programmatic sharing

Restriction rules

Exploring standard, custom, external, and big objects

Standard objects

Custom objects

External objects

Big objects

Object relationship types

Overcoming data skew

Ownership skew

Account skew

Lookup skew

Data skew summary

Bringing it all together with data modeling

Data modeling example and explanation

Summary

Practice questions

Answers

Further reading

3

Master Data Management

Introducing MDM

Key terms

Implementing MDM

Source of record

Central registry

Consolidated golden record

Coexistence of the golden record

Which implementation method is best?

What has any of this got to do with Salesforce?

The golden record

What data should reside in the golden record?

Salesforce holding the golden record associations

Middleware holding the golden record associations

A separate system holding the golden record associations

Using Salesforce Connect to pull in data in real time for read-only purposes

Consolidating data attributes from multiple sources

Preserving traceability and business rule context

Event Monitoring

Setup Audit Trail

Field History Tracking

Field Audit Trail

Custom metadata types and custom settings

Summary

Practice questions

Answers

Further reading

4

Salesforce Data Management

Analyzing Salesforce license types and access to objects

Standard platform licensing

Experience Cloud licensing

Licensing for Salesforce products not on the core platform

Full products versus Salesforce-managed packages

AppExchange and package licensing

Persisting data

Representing a single view of the customer on the Salesforce Platform

Elements of the Customer 360 platform

Pulling together data from multiple Salesforce instances

Salesforce Connect

Salesforce to Salesforce

Bulk API

Batch Apex

Summary

Practice questions

Answers

Further reading

5

Data Governance

Considerations for implementing a compliant data model

Enterprise data governance

Roles and responsibilities

Summary

Practice questions

Answers

Further reading

6

Understanding Large Data Volumes

Designing a scalable data model

Searching for Salesforce data

Data skew and its impacts on performance

Data virtualization

LDV performance mitigation strategies

Custom indexes

Skinny tables

Selective filter conditions

Divisions

Data archiving strategies

Big objects

Data Loader

ETL

Summary

Practice questions

Answers

Further reading

7

Data Migration

Understanding data movement and its considerations

Defining a process for migrating data

Define

Clean

Extract

Transform

Load

Test

De-duplicate

Enrich

Maintain

Loading high-quality data

Migrating Large Data Volumes to Salesforce

Exporting data from Salesforce

Data Export

Bulk API

PK chunking

Summary

Practice questions

Answers

Further reading

Section 2: Salesforce Data Architect Design

8

Accounts and Contacts

Understanding the Account and Contact model

Account Hierarchies

Introducing Person Accounts

Exploring the Contacts to multiple Accounts feature

Exploring objects associated with Accounts and Contacts

AccountContactRelation

AccountContactRole

Account Teams

Putting it all together

Revisiting Account Skew

Mitigating Account Skew

Summary

Practice questions

Answers

Further reading

9

Data APIs and Apex

How to call an API

Lightning Platform Data APIs

REST API

SOAP API

Bulk API

Apex Database operations

Batch Apex

Asynchronous Apex

Summary

Practice questions

Answers

Further reading

10

Tuning Performance

Skinny tables and other LDV mitigation techniques

Selective filter conditions

Divisions

Query and search optimization

Task locks

PK chunking to improve performance

Loading massive amounts of data

Summary

Practice questions

Answers

Further reading

11

Backup and Restore

Methods for backing up and restoring data on the Salesforce Lightning Platform

Introduction to metadata

What is data?

Why back up data and metadata?

Backing up data

Importing data

Backing up metadata

Importing metadata

AppExchange and external software that facilitates data backup and restoration

Summary

Practice questions

Answers

Further reading

12

Territory Management

Enterprise territory management overview

Territory

Territory Type

Territory Type Priority

Territory Model

Territory Model State

Territory Hierarchy

Implications of territory management on data model design and sharing records

Summary

Practice questions

Answers

Further reading

Section 3: Applying What We've Learned – Practice Questions and Revision Aids

13

Practice Exam Questions

Practice questions 1-20

Practice questions 21-40

Practice questions 41-60

Practice questions 61-80

Practice questions 81-100

Summary

14

Cheat Sheets

Database modeling and database design

Master data management

Salesforce data management

Data governance

Large data volumes

Data migration

Accounts and contacts

Summary

15

Further Resources

Data modeling and database design

Master data management

Salesforce data management

Data governance

Large data volumes

Data migration

Accounts and contacts

Data APIs and Apex

Tuning performance

Backup and restore

Territory management

Summary

16

How to Take the Exam

Webassessor

Signing up for a Webassessor account

Taking the exam in person

Taking the exam virtually

The result

Summary

17

Answers to Practice Questions

Answers for question set 1-20

Answers for question set 21-40

Answers for question set 41-60

Answers for question set 61-80

Answers for question set 81-100

Index

Other Books You May Enjoy

Preface

Salesforce skills, and particularly those of Salesforce architects, continue to grow in demand as the Salesforce ecosystem continues to grow all over the globe. This book focuses on one topic area of the Salesforce architect curriculum, namely data architecture. The Salesforce Certified Data Architect exam may seem a little daunting when reading the exam outline for the first time (I certainly thought so). But it needn't be. I was lucky to be able to pass the exam the first time, and that was possible by gathering information and going through the Salesforce documentation over several months. This book is the book I wish I'd had when studying for the exam, because it specifically covers the material necessary for the theory side of the exam.

We'll start by going through each of the areas covered in the exam outline in turn, from data modeling, master data management, Salesforce data management, data governance and large data volumes to data migration. Understanding these is pivotal to getting the theory tested in the exam covered. Moreover, the theory can be directly applied to the solutions you build and maintain in your role as a Salesforce architect.

We then turn our attention to applying concepts through additional topics that, while not always directly called out in the syllabus, will round out your knowledge of applying Salesforce data principles. These include a deeper dive into accounts and contacts, APIs and Apex, tuning performance, backup and restore, and territory management. Each of these topics will explain how the data model, sharing, and therefore any solutions built with these topics in mind are affected.

Lastly, we'll look at practice questions (with answers) and some revision aides. By the end of this book, you'll have covered the topics required to pass the Salesforce Certified Data Architect exam and also be able to implement Salesforce data design best practices in your day-to-day role as a Salesforce architect.

Who this book is for

This book is for both aspiring Salesforce architects and those already familiar with Salesforce data architecture who want to pass the Salesforce Certified Data Architect exam and have a reference guide to revisit the material as part of the day-to-day job. Working Salesforce Platform knowledge is assumed, and an understanding of Salesforce architectural concepts would be beneficial.

What this book covers

Chapter 1, Introducing the Salesforce Data Architect Journey, introduces the credential, by providing a high-level overview of the topic areas and exam curriculum, as well as outlining the rest of the book.

Chapter 2, Data Modeling and Database Design, covers how the Salesforce data model is architected, the design decisions behind that, and how the model affects sharing and security.

Chapter 3, Master Data Management, introduces the subject of Master Data Management (MDM), and how to effectively design and implement an MDM strategy on the Salesforce Platform.

Chapter 4, Salesforce Data Management, covers Salesforce license types, object access, and how to govern the data on the platform when architecting performant solutions that combine data from one or more Salesforce instances.

Chapter 5, Data Governance, covers the concepts behind building compliant solutions and how the Salesforce Platform can underpin an enterprise data governance strategy.

Chapter 6, Understanding Large Data Volumes, delves into considerations that apply to larger/massive amounts of data (referred to as large data volumes) and how performance on the platform is affected, as well as techniques for mitigating such scenarios.

Chapter 7, Data Migration, looks at getting data in and out of the platform in a planned and optimal way.

Chapter 8, Accounts and Contacts, covers the account/contact model, including person accounts and contacts to multiple accounts, account skew, and the implications this has on the performance of queries and reports.

Chapter 9, Data APIs and Apex, gets into the various Salesforce Platform APIs, Apex operations (including database, batch, and asynchronous), and how to deploy them effectively when designing data operations.

Chapter 10, Tuning Performance, looks at the various methods available to tune performance when designing scalable applications on the Salesforce Platform.

Chapter 11, Backup and Restore, outlines the methods available to get data out of and back into the Salesforce Platform, focussing on data backup and restore.

Chapter 12, Territory Management, introduces Salesforce Territory Management and how it pertains to the data model and usage design on the Salesforce Platform.

Chapter 13, Practice Exam Questions, presents exam-like questions to further put into practice the theory you will have learned and bolster your understanding of the topic areas of the exam curriculum.

Chapter 14, Cheat Sheets, introduces handy reference cheat sheets that provide a quick reference guide for aiding revision or for the day-to-day job.

Chapter 15, Further Resources, highlights links to other information that can enhance your understanding of the material we cover in this book.

Chapter 16, How to Take the Exam, describes what you will need to do to take the exam.

Chapter 17, Answers to Practice Questions, provides the answers to the questions provided in Chapter 13, Practice Exam Questions.

To get the most out of this book

You will need to be familiar with general Salesforce terminology and have a working knowledge of Salesforce in order to fully grasp the concepts covered in this book. All topics covered assume basic familiarity with the theory behind the Salesforce multitenant architecture.

We cover how to sign up for and obtain a Salesforce Developer Edition instance, which can be used for all topics, examples, and scenarios covered in this book.

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Section 1: Salesforce Data Architect Theory

By the end of this section of the book, you will have covered all the theory necessary to pass the exam. Each topic will have been covered in sufficient depth so that you will be able to answer questions as required when attempting the credential. You will also be able to come back to this part of the book time and time again after having passed the exam as the topics outlined will become a handy reference in your day-to-day job as a Salesforce Data Architect.

This section comprises the following chapters:

Chapter 1, Introducing the Salesforce Data Architect JourneyChapter 2, Data Modeling and Database DesignChapter 3, Master Data ManagementChapter 4, Salesforce Data ManagementChapter 5, Data GovernanceChapter 6, Understanding Large Data VolumesChapter 7, Data Migration

1

Introducing the Salesforce Data Architect Journey

The Salesforce Certified Data Architect credential is an important part of every Salesforce Architect's certification journey. It forms a constituent part of the Application Architect domain of the Certified Technical Architect credential, but it can stand alone, given the varying complexities and knowledge required to pass the exam. As architects, we're entrusted to build scalable foundations that our users can execute effectively upon, and data is the life-blood of a business. Understanding the relationship, quirks, and considerations of data and the Salesforce platform is crucial for designing applications that give users value. Passing this credential demonstrates advanced knowledge of these concepts. This book will arm you with the theory and skills necessary to pass the exam.

In this chapter, we'll learn about the Salesforce Certified Data Architect credential by covering the various curriculum areas and why they are important to understand to not just pass the exam, but also excel in this aspect of the day-to-day role of a Salesforce Architect.

Next, we'll get an overview of the learning journey covered in this book.

By the end of this chapter, you'll be able to understand the topic areas that constitute the credential, know what a Salesforce Data Architect is, and understand how the learning journey throughout this book is structured.

In this chapter, we'll cover the following topics:

What is the Data Architecture and Management credential?Introducing the examProfile of a Salesforce Data ArchitectIntroducing the learning journey

What is the Data Architecture and Management credential?

The Salesforce Certified Data Architect credential is one of several introduced by Salesforce to initially address three main challenges:

As Salesforce implementations increase in size and complexity, there is an increasing need for good data management, including best practices in data architecture and management in Salesforce. Data is the life-blood for many businesses, and the architecture of Salesforce as the platform to hold that data is important.There was a huge gap in the knowledge required between the Certified Technical Architect credential and the other credentials available. The only prerequisite for CTA in the past was that you had to hold the Salesforce Certified Administrator certification and answer a multiple-choice pre-exam!Not everyone wants to necessarily be a full-blown Salesforce Certified Technical Architect. Instead, they may want to focus on one or more specific technical domains or aspects of the Salesforce platform.

Simply put, this credential puts the focus on the data architecture aspects of the Salesforce platform. Candidates who pass this credential will have had to learn about the wide range of theory, techniques, and considerations that constitute the credential syllabus, which is based on the real-world knowledge that's required of a Data Architect on the Salesforce Customer 360 platform. By learning everything that's required to pass the Salesforce Certified Data Architect credential, candidates will have a toolkit of knowledge and understanding to draw from, improving their ability to deliver solutions while considering the data aspects of the Salesforce platform.

Introducing the exam

The exam format consists of 60 multiple-choice questions, and candidates are given 105 minutes to complete the exam. The passing score that's required at the time of writing is 58%, and there are no written prerequisites for the exam (although, as you will discover quite quickly, it is extremely challenging to dive straight into this exam without the required learning and foundational knowledge of the Salesforce platform). Those unfamiliar with the Salesforce platform will struggle with many of the concepts introduced in this book, so it would be more practical to have experience in the platform at a sufficient capacity to understand how the data model works, what standard objects are available, and so on. This would typically equate to a few years of working with the platform, but this is subjective based on previous experience.

Breaking down the question count, testing time, and passing score required, we can deduce the following:

We have 1 minute and 45 seconds to answer each question. We require 35 correct answers to pass the exam.

The exam is taken virtually, either at a test center or online, both using Webassessor. The mechanics of this will be covered toward the end of this book.

Preparing for Success

As you most likely already know, resources are available online such as Trailhead (https://trailhead.salesforce.com) – specifically, the Data Architect and Management Trailmix (https://trailhead.salesforce.com/en/users/strailhead/trailmixes/architect-data-architecture-and-management) – and blogs that cover the theory around a specific topic. To bolster your learning journey, I'd like to introduce some habits that you can employ to boost your potential for success.

Playground environments

Salesforce provides free Developer Edition orgs (sometimes referred to as DE orgs) that have many of the paid-for features of the core Salesforce platform (so this won't include Marketing Cloud or Tableau, for example). These allow candidates to try out many of the concepts explained in this book in a real Salesforce environment to explore what the real implications of a particular concept or feature are. For example, it is entirely possible to create an external object that interacts with an external data source so that we can see what the usability and other limitations are when interacting with off-platform data in this way. I would fully encourage you to have at least one DE org in your learning toolkit. You can sign up for a DE org at https://developer.salesforce.com/signup.

Documenting designs and design decisions

Another habit to aid in the learning process and beyond is to start documenting the following:

ArtifactsDesign decisions

While it may not be an end goal for everyone, the Certified Technical Architect (CTA) review board exam requires candidates to produce several artifacts. These include a data model, system integration landscape, actors/licenses, role hierarchy, and so on.

One of the most crucial artifacts to produce is the data model because it conveys how information is linked together, where objects are used, the expected data volumes, data owners, org-wide default sharing, and where Large Data Volumes (LDVs) may be a concern, which means that mitigations will need to be planned for. You should become comfortable with producing this artifact as you assess your requirements and produce solutions. Having the correct data model will ensure that you have a solid sharing and visibility strategy, reporting strategy, and integration strategy. It's little wonder that this is considered a core artifact of the CTA review board, given how crucial it is to effectively design a technical solution on the Salesforce Customer 360 platform.

Let's look at an example data model diagram. As we can quickly ascertain from this relatively simplistic example, a lot of information can be explained quite easily that you can understand using the key provided (which any good diagram will contain):

Figure 1.1 – Data model example

Design decisions are an important factor in any Salesforce solution. Salesforce comes with its own unique set of features and limitations that need to be considered and worked with, so getting into the habit of documenting such decisions and linking those back to individual requirements will prove very useful when you're answering questions on the implications of, say, a specific feature's requirements and its impacts on a solution. There's no prescribed format for this as such – I've seen examples of in-line annotations for a requirements document (which is the preferred method for some CTA candidates when they're taking the review board exam), and I've also seen Excel spreadsheets with line items for each requirement with functional considerations and technical considerations columns where such items are documented.

Other Salesforce credentials in the Application Architect domain

As you'll know, there are several Salesforce certifications for each of the CTA domains. Looking at the Application Architect domain specifically, the following credentials comprise it:

Figure 1.2 – The Application Architect domain

You may already have some or all the other credentials in the Application Architect domain. For those of you who may not, I strongly encourage you to gain your Platform App Builder and Platform Developer 1 credentials as you go through your journey as a Salesforce Data Architect. Both of these exams contain foundational questions related to data on the platform and can act as another enabler for success with the Salesforce Certified Data Architect credential.

The Sharing and Visibility Designer credential will have some overlap with the Data Architect credential as data and sharing on the Salesforce platform are relatively intertwined. When you complete this credential, I suggest moving on to the Sharing and Visibility Designer credential because some of the concepts that will be introduced in this book are pertinent to that credential. You can see how the Application Architect credentials relate and why it is useful to gain the foundational learning that's introduced in the Platform Developer 1 and Platform App Builder credentials if you have not already done so (although these are not strict prerequisites to taking the Data Architect exam). The Application Architect domain credential is automatically awarded upon completing the constituent exams, as per the preceding diagram.

Now that we know about the credential and what the exam looks like (including some tips and habits to help bolster learning), let's break down the Salesforce Data Architect job profile.

Profile of a Salesforce Data Architect

According to the Salesforce Certified Data Architect Exam Guide (located at https://trailhead.salesforce.com/help?article=Salesforce-Certified-Data-Architecture-and-Management-Designer-Exam-Guide), a Salesforce Data Architect is someone who does the following:

… assesses the architecture environment and requirements and designs sound, scalable, and performant solutions on the Customer 360 Platform as it pertains to enterprise data management. The candidate is knowledgeable about information architecture frameworks covering major building blocks, such as data sourcing, integration/movement, persistence, master data management, metadata management and semantic reconciliation, data governance, security, and delivery. 

The candidate also has experience assessing customers requirements in regards to data quality needs and creating solutions to ensure high-quality data (for example, no duplicates, correct data) and can also recommend organizational changes to ensure proper data stewardship. The candidate has experience communicating solutions and design trade-offs to business stakeholders.

Let's break this definition down a little.

The first paragraph of that definition contained a lot of terms, but ultimately, it describes someone who can understand the requirements and applies data architecture principles and experience when formulating a solution or design. To me, this is part-and-parcel of our day job: understanding requirements and designing solutions. There is also mention of performance, data management, security, scalability, and governance. The second paragraph focuses on data quality and stewardship. All these aspects are covered in this book.

When we turn our attention to what the profile of a Data Architect is, a lot of parallels can be drawn to the humble Salesforce administrator, consultant, or architect – we listen to what our stakeholders want and design solutions that address those requirements, all while being mindful of the considerations and trade-offs that may present themselves along the way.

A Data Architect applies their knowledge of the data architecture of the Salesforce Customer 360 platform, including its features and their impact on the system when producing designs or solutions, such as the following:

Sharing and security impacts based on the relationship choice between objectsLarge data volume considerations and mitigationsKnowing what type of object to use where (standard, custom, big, or external)IndexingPerformanceData stewardship and governanceLoading and extracting data from the platform, and the methods available to affect the performance of these

With the definition of the profile of a Salesforce Data Architect broken down a little, we can turn our attention to the learning journey that will be outlined in this book.

Introducing the learning journey

Throughout this book, the certification learning journey will be broken down into the theory and the designer parts of the exam. The theory will align closely with the curriculum that's described in the exam guide, with the designer section dedicated to learning about the practical concepts referenced in the theory – for example, learning about Person Accounts and how they affect the data model and sharing thereof.

The learning journey starts with the theoretical concepts behind the exam:

Data Modeling and Database Design:Understanding how the Salesforce data model is architected, the design decisions behind that, and how the model affects sharing and security.Understanding the different types of objects and how these fit into the data model design strategy.Understanding data skew, which will provide you with an understanding of this concept in Salesforce.Master Data Management:Understanding how to effectively design and implement a Master Data Management (MDM) strategy on the Salesforce platform.Being able to articulate the concept of a golden record, preserve data traceability across multiple data sources, and understand how this affects the context that business rules run in.Salesforce Data Management:How Salesforce license types affect the data model and the sharing options available to work with. Understanding these, as well as how to govern the data on the platform, is crucial to designing scalable, performant solutions that combine data from one or more Salesforce instances.Data Governance:Being able to safeguard data on the Salesforce platform is a key part of the Salesforce Data Architect's role. This chapter covers the concepts behind building compliant solutions and how the Salesforce platform can underpin an enterprise data governance strategy.Large Data Volumes:Whilst the Salesforce platform can cope with large amounts of data, some considerations apply to larger/massive amounts of data (referred to as large data volumes) and how the performance on the platform is affected.This chapter covers LDV considerations and mitigations, as well as scalable data model design and data archiving strategies.Data Migration:How do you get good quality data into the Salesforce platform? How do you ensure loading large amounts of data is smooth, reliable, repeatable, and timely? How do you effectively export data from the Salesforce platform?

Next, we'll look at the designer concepts that apply practical knowledge and practices to hone the theory:

Accounts and Contacts:We will cover the Account/Contact model, including Person Accounts and Contacts to Multiple Accounts, account skew, and the implications this has on the performance of queries and reports.Data APIs and Apex:We will understand the various Lightning Platform APIs and Apex operations (including database, batch, and asynchronous), and how to deploy them effectively when designing data operations on the Salesforce Customer 360 Platform.Tuning Performance:We will learn about the various methods that are available for tuning performance when designing Salesforce applications on the Salesforce Customer 360 Platform.Backup and Restore:We will understand the methods that are available for getting data out of and back into the Salesforce platform while focusing on data backup and restore. This is useful when you're designing ETL and other solutions as part of an overall Salesforce IT estate.Territory Management:We will understand territory management and how it pertains to the data model and its usage design on the Salesforce Lightning Platform.

Lastly, there is a section of this book that's dedicated to exam success that focuses on the following:

Practice questions and answersCheatsheetsIntroduction to further reading on some of the concepts and topics mentioned in this bookAn overview of Webassessor, including how to sign up for and take the exam

Summary

In this chapter, we learned about why the Salesforce Certified Data Architect credential exists, the exam format, and the profile of a Salesforce Data Architect to truly understand why the concepts behind this exam are useful in your day job. Lastly, we covered this book's learning journey to set the tone for the rest of this book.

In Chapter 2, Data Modeling and Database Design, we will begin our learning journey by revisiting the Salesforce data model, how different objects affect it, as well as touching on concepts such as data skew and ownership skew. We'll cover how to effectively describe the Salesforce data model while considering sharing, record counts, and performance as appropriate.

Practice questions

Answer the following question to test your knowledge of this chapter:

What is the Salesforce Certified Data Architect credential?Why does the credential exist?What is the typical profile of a Salesforce Data Architect?

Further reading

Read the official Salesforce exam guide: https://trailhead.salesforce.com/help?article=Salesforce-Certified-Data-Architecture-and-Management-Designer-Exam-Guide.

2

Data Modeling and Database Design

In this chapter, we'll begin our journey into the theory behind the credential syllabus, starting with Data Modelling and Database Design. You will learn how a Salesforce data model is architected, the design decisions behind it, and how a data model you may create in your job as a Salesforce Data Architect affects sharing and security. We'll go over the Salesforce sharing model so that you have an overview of what is available when considering options around data access.

Next, we'll look at the different types of objects (such as standard, custom, big, and external), and how they fit into a data model design strategy. While we're there, we'll cover the different relationship types so that you can understand when to apply them.

Turning to performance, we'll cover data skew to provide you with an understanding of this concept in Salesforce. We'll then cover diagramming techniques so that you can begin to effectively design and represent Salesforce data models.

In this chapter, we'll be covering the following topics:

The Salesforce data modelUnderstanding Salesforce sharing and securityExploring standard, custom, external, and big objectsOvercoming data skewBringing it all together with data modeling

The Salesforce data model

Salesforce abstracts the underlying data structure in its database for a given customer org by providing a faux RDBMS view of the objects within it. For example, take the diagram you find when viewing the Sales Cloud ERM at https://architect.salesforce.com/diagrams/template-gallery/sales-cloud-overview-data-model:

Figure 2.1 – The Salesforce Sales Cloud data model

As we can see, a contact record will have an AccountId represented as a lookup (which would be a foreign key in RDBMS terminology). Take this example for Account and Contact from Schema Builder for a brand-new Developer Edition org:

Figure 2.2 – Account and Contact represented in Schema Builder in a brand-new Developer Edition org

See for Yourself

Feel free to sign up for a (completely free) Developer Edition Salesforce org at https://developer.salesforce.com/signup in order to follow along with the examples in this book, including exploring Schema Builder.

Salesforce would have you think that Account and Contact exist as two separate database tables (and indeed there would be a separate table for each standard or custom object in the schema). Indeed, it is perfectly normal to think about the objects in this way in your day-to-day work as a Salesforce Data Architect.

The truth is, however, that Salesforce has a few large, underlying database tables (one for objects, one for fields, one for data that maps to those objects and fields, pivot tables, and so on) that provide for a virtual data structure for each org that is materialized at runtime. One virtual storage area contains standard objects and standard fields, another contains standard objects and custom fields, and another contains custom objects and their custom fields. This is explained in further detail at https://developer.salesforce.com/wiki/multi_tenant_architecture. In essence, the standard object/standard fields storage area is populated when a new org is provisioned, and the custom storage areas are added to whenever a new custom object or custom field is added (no matter whether that custom field is added to a standard or custom object). This structure can therefore be represented as follows, imagining a custom field is added to each of the standard Account and Contact objects:

Figure 2.3 – Representation of the Salesforce database (object data only) with a custom field added to the Account and Contact standard objects

Let's now add a custom object to see how the virtual storage is affected and what that change looks like in Schema Builder:

Figure 2.4 – Representation of the Salesforce database (object data only) with a custom object added to the org and a custom field added to that new custom object

Figure 2.5 includes both the custom object and the custom field in the schema:

Figure 2.5 – Schema Builder with the representation of the newly added custom object and custom field

Armed with the