Hands-On Salesforce Data Cloud

Book description

Learn how to implement and manage a modern customer data platform (CDP) through the Salesforce Data Cloud. This practical book provides a concise yet comprehensive overview that shows Salesforce architects, administrators, and developers how to access, store, and manage real-time customer data with the Data Cloud and build out calculated, streaming, and visual insights.

Author Joyce Kay Avila also shows you how to leverage Salesforce's third-party platform integrations, including Snowflake and Amazon Web Services, to combine data from a variety of sources. You'll learn how to effectively communicate with both internal and external stakeholders about Salesforce Data Cloud and CDPs, identify use cases where the Data Cloud platform would be a good implementation solution, and utilize AI within the platform.

This book will help you:

  • Develop a plan to execute a CDP project
  • Create a Customer 360 Data Model
  • Set up Salesforce Data Cloud with user roles and permissions
  • Use Salesforce Data Cloud Data Cloud capabilities for identity resolution and segmentation
  • Learn Data Cloud best practices for use with Tableau and Salesforce Marketing Cloud
  • Connect Data Cloud to external data sources
  • Build out calculated, streaming, and visual insights
  • Leverage third-party platform integrations to extend a CDP project

Publisher resources

View/Submit Errata

Table of contents

  1. Brief Table of Contents (Not Yet Final)
  2. 1. Salesforce Data Cloud and CDP Origins
    1. Evolution of the Salesforce Data Cloud Platform
    2. Where the Salesforce Data Cloud Fits in the Salesforce Tech Stack
    3. Where CDP Fits in the Martech Stack
      1. Today’s Modern Martech Stack
      2. The Future of the Martech Stack
    4. The Customer Data Problem
      1. Known Data
      2. Unknown Audience’s Data
      3. Putting the Pieces Together
    5. Digital Marketing Cookies
      1. First-, Second-, and Third-Party Cookies
      2. The Future of Cookies
    6. Building a First-Party Data Strategy
      1. Extending the First-Party Data Strategy
      2. Data Clean Rooms and CDPs Working Together
    7. CDP Acquisition Approaches
      1. Build, Buy, or Compose?
      2. Narrowing the Focus
      3. Composable CDP versus CDP Suite
      4. Other Cost and Performance Considerations
    8. Summary
  3. 2. Foundations of the Salesforce Data Cloud
    1. Special Considerations for Architects
      1. Data-Driven Pattern Use Cases 
      2. Considerations for Building a Data-Driven Platform
      3. Salesforce Well-Architected Resources
      4. Data Cloud Technical Capability Map
    2. Data Cloud Key Functional Aspects
      1. General Key Data Concepts
      2. How Data Cloud Works Its Magic
      3. Connecting Multi-Clouds
      4. Salesforce AppExchange
    3. Under the Hood: Data Cloud Technical Details
      1. How Data Cloud is Architected on AWS Services
      2. Storage Layering
      3. Near Real Time Ingestions and Data Processing
    4. Unique Datastore Features
      1. Data Cloud Data Entities
      2. Bring Your Own Lake (BYOL)
      3. Data Spaces
  4. 3. Implementation Basics and First-Time Provisioning
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Data Cloud User Personas
      1. Data Cloud Platform Administrator and Platform User
      2. Data Cloud Platform Marketing Manager
      3. Data Cloud Platform Marketing Specialist
      4. Data Cloud Platform Data Aware Specialist
    3. First-time Data Cloud Platform Setup
      1. Configure Admin User
      2. Provision the Data Cloud Platform
      3. Create Profiles and Configure Additional Users
      4. Connect to Relevant Salesforce Clouds
    4. Managing Data Cloud Feature Access
      1. Create Data Cloud Custom Permission Sets
      2. Leverage Data Cloud Sharing Rules
    5. Summary
  5. 4. Data Cloud Menu Options
    1. Activation Targets
    2. Activations
    3. Calculated Insights
    4. Dashboards
    5. Data Action Targets
    6. Data Actions
    7. Data Explorer
    8. Data Lake Objects
    9. Data Model
    10. Data Share Targets
    11. Data Shares
    12. Data Spaces
    13. Data Streams
    14. Data Transforms
    15. Einstein Studio
    16. Identity Resolution
    17. Profile Explorer
    18. Reports
    19. Segments
    20. Data Cloud Activities Accessed Indirectly
    21. Summary
  6. 5. Data Ingestion and Storage
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Viewing Data Cloud Objects via Data Explorer
    3. Ingesting Data Sources via Data Streams
      1. Near Real-Time Ingest Connectors
      2. Streaming Ingest Connectors
      3. Batch Data Source Ingest Connectors - Salesforce Core Platforms
      4. Other Batch Data Sources Ingest Connectors
    4. Viewing Data Lake Objects
    5. Accessing Data Sources via Data Shares
    6. Summary
  7. 6. Data Modeling 
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Data Profiling
    3. Source Data Classification
      1. Data Descriptors
      2. Data Categories
      3. Immutable Date Field Data Type
      4. Data Categorization 
    4. The Salesforce Data Cloud Standard Model
      1. Primary Subject Areas
      2. Extending the Data Cloud Standard Data Model
    5. Summary
  8. 7. Data Transformations
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Streaming Data Transformations
      1. Streaming Data Transformation Use Cases
      2. Setting Up and Managing Streaming Data Transformations
      3. Streaming Data Transform Functions and Operators
      4. Streaming Transforms vs Batch Transforms
    3. Batch Data Transformations
      1. Batch Data Transformation Use Cases
      2. Setting Up and Managing Batch Data Transformations
      3. Batch Data Transform Node Types
      4. Batch Data Transformation Limitations and Best Practices
      5. Data Transform Jobs
    4. Summary
  9. 8. Data Mapping
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Data Mapping
      1. Required Mappings
      2. The Field Mapping Canvas
      3. Relationships Between Data Model Objects
    3. Using Data Explorer to Validate Results 
    4. Summary
  10. 9. Identity Resolution
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Identity Resolution Rulesets
      1. Creating Identity Rulesets
      2. Deleting Identity Rulesets
      3. Ruleset Statuses for the Current Job
      4. Ruleset Statuses for the Last Job
    3. Ruleset Configurations Using Matching Rules
      1. Types of Matching Rules
      2. Configuring Identity Resolution Matching Rules
      3. Default Matching Rules
      4. Using Party Identifier in Matching Rules
    4. Ruleset Configurations Using Reconciliation Rules
      1. Default Reconciliation Rules
      2. Setting a Default Reconciliation Rule
      3. Applying a Different Reconciliation Rule to a Specific Field
      4. Reconciliation Rule Warnings
    5. Anonymous and Known Profiles in Identity Resolution
    6. Identity Resolution Summary
    7. Validate and Optimize Identity Resolution
    8. Summary
  11. About the Author

Product information

  • Title: Hands-On Salesforce Data Cloud
  • Author(s): Joyce Kay Avila
  • Release date: November 2024
  • Publisher(s): O'Reilly Media, Inc.
  • ISBN: 9781098147860