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Learn everything you need to become a successful data architect on the Salesforce platform

Key Features

  • Adopt best practices relating to data governance and learn how to implement them
  • Learn how to work with data in Salesforce while maintaining scalability and security of an instance
  • Gain insights into managing large data volumes in Salesforce

Book Description

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.

What you will learn

  • Understand the Salesforce data architecture
  • Explore various data backup and archival strategies
  • Understand how the Salesforce platform is designed and how it is different from other relational databases
  • Uncover tools that can help in data management that minimize data trust issues in your Salesforce org
  • Focus on the Salesforce Customer 360 platform, its key components, and how it can help organizations in connecting with customers
  • Discover how Salesforce can be used for GDPR compliance
  • Measure and monitor the performance of your Salesforce org

Who this book is for

This book is for aspiring architects, Salesforce admins, and developers. You will also find the book useful if you're preparing for the Salesforce Data Architecture and Management exam. A basic understanding of Salesforce is assumed.

Table of Contents

  1. Salesforce Data Architecture and Management
  2. Contributors
  3. About the author
  4. About the reviewers
  5. Preface
    1. Who this book is for
    2. What is this book covers
    3. To get the most out of this book
    4. Download the color images
    5. Conventions used
    6. Get in touch
    7. Share Your Thoughts
  6. Section 1: Data Architecture and Data Management Essentials
  7. Chapter 1:Data Architect Roles and Responsibilities
    1. Defining architecture
    2. Exploring architecture roles
    3. Business architect
    4. Data architect
    5. Solution architect
    6. Domain architects
    7. Why is data architecture important?
    8. The benefits of data architecture
    9. Data architect responsibilities
    10. Data architect skills
    11. Technical skills
    12. Soft skills
    13. Becoming a data architect
    14. A day in the life of a data architect
    15. Summary
    16. Questions
    17. Further reading
  8. Chapter 2: Understanding Salesforce Objects and Data Modeling
    1. Exploring data modeling
    2. What is a data model?
    3. Normalization
    4. Denormalization
    5. Design principles for data modeling
    6. Reviewing object relationships
    7. Differences between SQL and SOQL
    8. Understanding Salesforce architecture
    9. Multi-tenancy
    10. Metadata-driven architecture
    11. New releases
    12. Introducing Salesforce objects
    13. Standard objects
    14. Custom objects
    15. Big objects
    16. External objects
    17. Fields in Salesforce
    18. Summary
    19. Questions
    20. Further reading
  9. Chapter 3: Understanding Data Management
    1. What is data?
    2. Is data valuable?
    3. Introducing data management
    4. Benefits of data management
    5. Challenges of data management
    6. Introducing the data life cycle
    7. Data creation
    8. Storage
    9. Usage
    10. Archival
    11. Purge
    12. Data life cycle – A Salesforce example
    13. Data management operating models
    14. Centralized operating model
    15. Decentralized operating model
    16. Hybrid operating model
    17. Learning data management best practices
    18. Understanding data and metadata
    19. Introducing data backup and recovery
    20. Reasons to back up data
    21. Devising a strategy for data backup
    22. Costs
    23. Security
    24. Service levels
    25. Ease of use
    26. Solution comprehensiveness
    27. Performance
    28. Types of backup
    29. Restoring data
    30. Missing data
    31. Sandbox seeding
    32. Citizen development
    33. Nuances of the restore process
    34. Backup and recovery – tools of the trade
    35. Data Export Service
    36. Data Loader
    37. Odaseva
    38. OwnBackup
    39. Summary
    40. Questions
  10. Section 2: Salesforce Data Governance and Master Data Management
  11. Chapter 4: Making Sense of Master Data Management
    1. Understanding master data
    2. What is master data?
    3. The need for master data management
    4. Categories of data
    5. Solving problems via master data management
    6. Deciding what data is master data
    7. Multi-org scenario
    8. Defining Master Data Management (MDM)
    9. Reviewing the basics of data quality
    10. Implementing MDM
    11. Considerations for selecting an MDM solution
    12. The Golden Record
    13. Why is the Golden Record important?
    14. Detractors of the Golden Record
    15. MDM and CRM strategy
    16. Customer 360
    17. Common Information Model (CIM)
    18. Summary
    19. Questions
  12. Chapter 5: Implementing Data Governance
    1. Enterprise data governance
    2. What is data governance?
    3. Understanding the need for data governance
    4. Benefits of data governance
    5. Understanding the difference between data governance and data management
    6. Metadata management
    7. Guiding principles for data governance programs
    8. The keys to the kingdom – making your data governance program successful
    9. Successfully governing Salesforce
    10. Technical change control
    11. Business backlog
    12. Assessing the current state of data governance
    13. Assessing the current landscape
    14. Need for data governance maturity models
    15. Data privacy and privacy laws
    16. Understanding the need for privacy laws
    17. Understanding the business risks
    18. Global Data Protection Regulation (GDPR)
    19. California Consumer Protection Act (CCPA)
    20. Salesforce tools for implementing privacy laws
    21. Putting it all together
    22. Problem
    23. The solution approach
    24. Summary
    25. Questions
    26. Further reading
  13. Chapter 6: Managing Performance
    1. Salesforce Platform performance
    2. Importance of performance monitoring
    3. Reasons for performance-related issues
    4. Performance tools
    5. URL suffixes
    6. Speedtest
    7. Salesforce Optimizer
    8. Salesforce Shield’s event monitoring
    9. Salesforce Page Optimizer
    10. Salesforce Lightning Inspector
    11. Salesforce reports
    12. Query Plan tool
    13. Improving performance
    14. Conducting performance testing in Salesforce
    15. Approaching performance testing in Salesforce
    16. Conducting a successful performance test
    17. Monitoring performance
    18. What to monitor?
    19. Summary
    20. Questions
    21. Further reading
  14. Section 3: Large Data Volumes (LDVs) and Data Migrations
  15. Chapter 7: Working with Large Volumes of Data
    1. Revisiting databases
    2. Relational databases
    3. Non-relational databases
    4. Large Data Volumes (LDVs)
    5. Knowing the implications of LDVs
    6. Multitenancy and search architecture
    7. Considerations for integrating or migrating LDVs
    8. Preventing LDV scenarios
    9. Optimizing LDV operations
    10. Salesforce Connect and external objects
    11. Ways to connect
    12. Introducing big objects
    13. Benefits of big objects
    14. Considerations for big objects
    15. Use cases for big objects
    16. Summary
    17. Questions
    18. Further reading
  16. Chapter 8: Best Practices for General Data Migration
    1. Assessing data
    2. Components of a data migration assessment
    3. The Preparation phase
    4. Best practices
    5. The Execution phase
    6. Best practices
    7. Tools for loading data into Salesforce
    8. Data Import Wizard (DIW)
    9. Salesforce Data loader
    10. Understanding APIs
    11. The SOAP API
    12. The Bulk API
    13. The REST API
    14. The Streaming API
    15. Summary
    16. Questions
    17. Further reading
  17. Assessments
    1. Chapter 1 – Data Architect Roles and Responsibilities
    2. Answers
    3. Chapter 2 – Understanding Salesforce Objects and Data Modeling
    4. Answers
    5. Chapter 3 – Understanding Data Management
    6. Answers
    7. Chapter 4 – Making Sense of Master Data Management
    8. Answers
    9. Chapter 5 – Implementing Data Governance
    10. Answers
    11. Chapter 6 – Managing Performance
    12. Answers
    13. Chapter 7 – Working with Large Volumes of Data
    14. Answers
    15. Chapter 8 – Best Practices for General Data Migration
    16. Answers
    17. Why subscribe?
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