This Salesforce Data Cloud training program designed to equip professionals with essential skills in data management and integration within the Salesforce ecosystem. This comprehensive course delves into key aspects such as data governance, data quality, and the integration of external data sources, providing participants with a robust understanding of how to leverage Salesforce Data Cloud effectively. Participants will learn advanced techniques for managing large volumes of data, ensuring its accuracy, security, and accessibility across various Salesforce applications. The training covers strategies for optimizing data workflows, enhancing data visualization capabilities, and utilizing artificial intelligence tools for data-driven decision-making processes.

Course Objectives:

After completing this module, you'll be able to:

• Learn to integrate external data sources seamlessly with Salesforce for comprehensive data management.
• Implement strategies to ensure data accuracy, consistency, and reliability across Salesforce platforms.
• Develop skills in establishing data governance frameworks to maintain data security and compliance.
• Explore tools and techniques for leveraging Salesforce's analytics capabilities to derive actionable insights from data.
• Gain proficiency in using data-driven insights to make informed decisions and drive business outcomes.
• Understand how to incorporate artificial intelligence features within Salesforce Data Cloud for enhanced automation and predictive analytics

Course content

Introduction to Salesforce Data Cloud 

• Define Salesforce Data Cloud
• Explore Core Capabilities and Benefits
• Navigate Key Features and Functionality
• Examine Data Cloud Use Cases
• Review Provisioning and Configuration Options
• Identify Roles and Permissions

Data Modeling Overview 

• Define Key Data Modeling Terminology
• Identify Data Modeling Objects, Fields, and Relationships
• Compare Normalized and Denormalized Data Structures
• Define Primary and Foreign Keys

Data Preparation 

• Review Data Usage Ethics
• Identify Data Sources
• Log Data Using a Data Dictionary

Data Modeling with Salesforce Data Cloud 

• Examine the Salesforce Customer 360 Data Model
• Compare Data Model Types Used in Data Cloud
• Define Data Cloud Object Categorization
• Identify Functionality of Primary and Foreign Keys in Data Cloud

Data Ingestion 

• Define the Data Ingestion Process
• Examine Data Space Use Cases
• Identify Data Cloud Connectors and Data Sources
• Explore Data Ingestion Features in Data Cloud
• Define Batch and Streaming Data Transforms

Data Harmonization 

• Define Key Data Harmonization Concepts
• Understand the Value of Data Harmonization
• Explore Data Cloud Mapping Capabilities

Unified Profiles 

• Define Identity Resolution
• Review the Profile Unification Process
• Identify Key Differences Between a Unified Profile and Golden Record
• Configure Identity Resolution Rulesets, Match Rules, and Reconciliation Rules
• Inspect Identity Resolution Results

Data-Driven Insights 

• Define Calculated Insights
• Define Streaming Insights
• Identify Key Differences Between Calculated and Streaming Insights
• Review Options for Building Insights
• Examine Formula, Calculated Insight, Streaming Insight, and Segment Operator Use Cases

Data Segmentation and Data Actions 

• Define Key Data Segmentation Terminology
• Create Data Segments in Data Cloud
• Implement Calculated Insights and Suggested Values in Segmentation
• Publish Data Segments Using Activations
• Trigger Targeted Automations and Integrations Using Data Actions

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