Hands-On Salesforce Data Cloud

Hands-On Salesforce Data Cloud

by Joyce Kay Avila
Released August 2024
Publisher(s): O'Reilly Media, Inc.
ISBN: 9781098147860

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Book description

Learn how to implement and manage a modern customer data platform (CDP) through the Salesforce Data Cloud. This practical book provides a comprehensive overview that shows architects, administrators, developers, data engineers, and marketers how to ingest, store, and manage real-time customer data with the Data Cloud.

Author Joyce Kay Avila demonstrates how to use Salesforce's native connectors, canonical data model, and built-in trust layer to accelerate your time to value. You'll learn how to leverage Salesforce's no-code / low-code functionality to expertly build a Data Cloud foundation that allows you to utilize AI to its fullest, not only within the Salesforce platform but also with third-party machine learning services like AWS SageMaker and Google Vertex.

This book will help you:

  • Develop a plan to execute a CDP project effectively and efficiently
  • Connect Data Cloud to external data sources and build out a Customer 360 Data Model
  • Leverage data sharing capabilities with Snowflake, BigQuery, Databricks, and Azure
  • Use Salesforce Data Cloud capabilities for identity resolution and segmentation
  • Create calculated, streaming, visualization, and predictive insights
  • Use Data Graphs to power Salesforce Einstein capabilities
  • Learn Data Cloud best practices for all phases of the development lifecycle

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Table of contents

  1. Foreword
  2. 1. Salesforce Data Cloud 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. Data Spaces
      5. Application Lifecycle Management with Sandboxes
      6. Salesforce AppExchange and Data Kits
    3. Under the Hood: Data Cloud Technical Details
      1. How Data Cloud is Architected on AWS Services
      2. Storage Layering
      3. Near Real-Time Ingestion and Data Processing
    4. Unique Datastore Features
      1. Data Cloud Data Entities
      2. Starter Data Bundles
    5. Summary
  4. 3. Business Value Activities
    1. Achieving Goals with Data and AI Democratization
    2. Building Your Data Cloud Vocabulary
    3. Value Creation Process
    4. Data Cloud Key Value Activities
      1. CRM Enrichments
      2. LLM Grounding Resource for Structured Data
      3. Augment LLM Search with Data Graphs and Vector Databases
      4. Data Actions & Data Cloud-Triggered Flows
      5. Activation of Segments
      6. Predictive AI Machine Learning Insights
      7. Analytics and Intelligent Data Visualization
      8. Unified Consent Repository
      9. Programmatically Extract Data
      10. Bi-directional Data Sharing with External Data Platforms
      11. Link Custom Large Language Models (BYOLLM)
      12. Other Key Value Activities
      13. What the Data Cloud is Not
    5. Value by Functional Roles
      1. Value at the Highest Granular Level
      2. Value at the Aggregate Level
      3. Other Critical Functional Roles
      4. Change Management Process: A Necessary Ingredient
      5. Value of a Salesforce Implementation Partner
      6. User Stories and Project Management
      7. Who Decides
    6. Value in Action: Industry Focus
      1. Travel, Transportation and Hospitality Industry
      2. Other Industries
    7. Summary
  5. 4. 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 Admin and Data Cloud User
      2. Data Cloud for Marketing Admin
      3. Data Cloud for Marketing Manager
      4. Data Cloud for Marketing Specialist
      5. Data Cloud for Marketing 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. Beyond the Basics: Managing Feature Access
      1. Create Data Cloud Custom Permission Sets
      2. Leverage Data Cloud Sharing Rules
    5. Summary
  6. 5. Data Cloud Menu Options
    1. Core Capabilities
      1. Activation Targets
      2. Activations
      3. Calculated Insights
      4. Consumption Cards
      5. Dashboards
      6. Data Action Targets
      7. Data Actions
      8. Data Explorer
      9. Data Graphs
      10. Data Lake Objects
      11. Data Model
      12. Data Share Targets
      13. Data Shares
      14. Data Spaces
      15. Data Streams
      16. Data Transforms
      17. Einstein Studio (aka Model Builder)
      18. Identity Resolution
      19. Profile Explorer
      20. Reports
      21. Segments
    2. Summary
  7. 6. 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. Batch Data Source Ingest Connectors - Salesforce Clouds
      3. Batch Data Sources Ingest Connectors - Cloud Storage
      4. External Platform Connectors
      5. Other Connectors for Batch Ingestion
      6. Deleting Ingested Records from Data Cloud
    4. Viewing Data Lake Objects
    5. Accessing Data Sources via Data Federation
    6. Summary
  8. 7. 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 and DateTime Fields
      4. Data Categorization
    4. Salesforce Data Cloud Standard Model
      1. Primary Subject Areas
      2. Extending the Data Cloud Standard Data Model
    5. Salesforce Consent Data Model
      1. Global Consent
      2. Engagement Channel Consent
      3. Contact Point Consent
      4. Data Use Purpose Consent
      5. Consent Management by Brand
      6. Consent APIs
    6. Summary
  9. 8. 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
  10. 9. 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
  11. 10. 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
  12. 11. Consuming and Actioning Data Cloud Data
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Data Cloud Insights
      1. Creating Insights
      2. Using Insights
    3. Data Cloud CRM Enrichments
      1. Related List Enrichments
      2. Copy Field Enrichments
    4. Data Actions and Data Cloud-Triggered Flow
      1. Define a Data Action Target
      2. Select the Data Action Primary Object
      3. Specify the Data Action Event Rules
      4. Define the Action Rules for the Data Action
      5. Enriching Data Actions with Data Graphs
    5. Extracting Data Programmatically
    6. Summary
  13. 12. Segmentation and Activation
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Segmentation and Activation Explained
    3. Define Activation Targets
    4. Create a Segment
      1. Segment Builder User Interface
      2. Einstein Segment Creation
      3. Segments Built through APIs
      4. Advanced Segmentation
    5. Publish a Segment
    6. Activate a Segment
      1. Contact Points
      2. Activation Direct and Related Attributes
      3. Activation Filters
      4. Calculated Insights in Activation
      5. Activation Refresh Types
      6. Troubleshooting Activation Errors
    7. Segment-Specific Data Model Objects
      1. Segment Membership DMOs from Published Segments
      2. Audience DMOs from Activated Segments
    8. Querying and Reporting for Segments
    9. Best Practices for Segmentation and Activation
    10. Summary
  14. 13. Einstein 1 Platform and the Zero Copy Partner Network
    1. Getting Started
      1. Pre-Work
      2. What You Should Know
    2. Einstein
    3. Einstein 1 Platform
      1. Einstein Model Builder
      2. Einstein Prompt Builder
      3. Einstein Copilot Builder
    4. Augmenting LLM Search
      1. Using Data Graphs for Near Real-Time Searches
      2. Using Vector Databases for Unstructured Data
    5. Zero Copy Partner Network
      1. Traditional Methods of Sharing Data
      2. Zero Copy Technology Partners
      3. Bring Your Own Lake (BYOL)
      4. Bring Your Own Model (BYOM)
    6. Recap
    7. Summary
      1. Roadmap Themes for the Data Cloud Platform
      2. Continuing the Learning Journey
      3. Keep Blazing the Trail
  15. A. Guidance for Data Cloud Implementation Plan
    1. General Guidelines
    2. Evaluation Phase
    3. Discovery and Design Phases
    4. Implementation and Testing
  16. About the Author

Product information

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