Data-Cloud-Consultant
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Data Cloud Consultant (Data-Cloud-Consultant)
The Salesforce Certified Data Cloud Consultant program teaches core Data Cloud concepts, data modeling, segmentation, governance, and analytics, enabling consultants to design and implement scalable data solutions on the Salesforce platform.
105
Minutes
60
Questions
65/100
Passing Score
$200
Exam Cost
Who Should Take This
Ideal for Salesforce administrators, analysts, or junior consultants with 1–3 years of experience who aim to expand their expertise into data‑driven solutions. They seek to master data architecture, segmentation strategies, governance best practices, and analytics to deliver measurable business value for clients.
What's Covered
1
Domain 1: Data Cloud Fundamentals
2
Domain 2: Data Modeling
3
Domain 3: Segmentation
4
Domain 4: Data Governance
5
Domain 5: Analytics
6
Domain 6: Integration
7
Domain 7: Implementation
8
Domain 8: Use Cases and Best Practices
What's Included in AccelaStudy® AI
Adaptive Knowledge Graph
Practice Questions
Lesson Modules
Console Simulator Labs
Exam Tips & Strategy
20 Activity Formats
Course Outline
64 learning goals
1
Domain 1: Data Cloud Fundamentals
2 topics
Architecture and Concepts
- Identify Data Cloud architecture including data model data spaces data streams identity resolution and activation targets
- Configure Data Cloud data spaces including namespace settings object permissions and data sharing rules for multi-tenant operations
- Configure data model objects including data lake objects DMO mappings and calculated insights for unified customer profiles
- Analyze Data Cloud architecture to design data ingestion strategies supporting multi-source customer data unification
Data Ingestion
- Identify data ingestion methods including connectors streaming APIs batch imports and Marketing Cloud data for source connectivity
- Configure data stream connectors including Salesforce CRM connector MuleSoft connector and cloud storage ingestion for data flow
- Configure batch and streaming ingestion including file upload schedules API event streams and webhook listeners for data pipelines
- Analyze data source requirements to design ingestion architectures balancing real-time and batch processing for unified profiles
2
Domain 2: Data Modeling
2 topics
Data Model Objects
- Identify DMO types including individual profile engagement event and other objects with their relationships in the data model
- Configure data model objects including field mappings relationship definitions and data type transformations for schema alignment
- Configure calculated insights including SQL-based transformations aggregate calculations and derived attributes for enrichment
- Analyze data modeling requirements to design DMO structures supporting segmentation activation and analytics use cases
Identity Resolution
- Identify identity resolution concepts including match rules reconciliation rules priority settings and merge behavior for profiles
- Configure identity resolution rulesets including exact match fuzzy match and normalized match rules for cross-source deduplication
- Configure reconciliation rules including source priority most recent and most frequent strategies for unified profile creation
- Analyze identity resolution outcomes to evaluate match rates false positive rates and recommend ruleset tuning for accuracy
3
Domain 3: Segmentation
2 topics
Segment Creation
- Identify segmentation features including segment types attribute filters engagement filters and nested segment logic for targeting
- Configure segments using visual segment builder including attribute conditions engagement rules and time-based filters for audiences
- Configure calculated insights for segmentation including RFM scoring lifetime value calculation and propensity modeling inputs
- Analyze segmentation requirements to design audience strategies combining behavioral demographic and engagement data for targeting
Segment Activation
- Identify activation targets including Marketing Cloud Advertising Studio Google Ads Meta and custom webhook destinations for outreach
- Configure activation targets including destination setup field mapping refresh schedules and audience sync for campaign execution
- Configure activation workflows including segment scheduling incremental updates and full refresh cycles for timely audience delivery
- Analyze activation requirements to design multi-channel audience distribution strategies optimizing reach and personalization
4
Domain 4: Data Governance
2 topics
Consent Management
- Identify consent management features including consent objects purpose definitions and data processing restrictions for compliance
- Configure consent framework including purpose definitions consent capture flows and processing restriction enforcement for privacy
- Configure data subject rights including deletion requests access requests and data portability exports for regulatory compliance
- Analyze consent requirements to design governance frameworks supporting GDPR CCPA and other privacy regulations simultaneously
Data Quality
- Identify data quality dimensions including completeness accuracy consistency timeliness and validity for unified profile quality
- Configure data quality rules including field validation format standardization and duplicate detection for clean profile data
- Configure data quality monitoring including completeness dashboards accuracy metrics and anomaly detection for ongoing governance
- Analyze data quality metrics to recommend improvement strategies addressing gaps in completeness accuracy and consistency
5
Domain 5: Analytics
2 topics
Data Cloud Analytics
- Identify analytics capabilities including data explorer calculated insights data graphs and CRM Analytics integration for insights
- Configure data explorer queries including attribute analysis engagement trending and segment overlap analysis for data insights
- Configure CRM Analytics integration including dataflows datasets and dashboards consuming Data Cloud data for advanced analytics
- Analyze analytics requirements to design reporting strategies combining Data Cloud native tools with CRM Analytics for insights
Einstein and AI
- Identify AI features including Einstein predictions propensity scores and lookalike modeling using Data Cloud unified profile data
- Configure Einstein prediction models including outcome definitions training data selection and score deployment for targeting
- Configure lookalike audience modeling including seed segments feature selection and similarity thresholds for audience expansion
- Analyze AI model performance to evaluate prediction accuracy recommend retraining schedules and optimize targeting effectiveness
6
Domain 6: Integration
2 topics
Platform Connectors
- Identify Data Cloud connectors including Salesforce CRM MuleSoft AWS S3 Google Cloud and Azure Blob for data source connectivity
- Configure CRM connector including object selection field mapping sync frequency and conflict resolution for Salesforce data ingestion
- Configure external connectors including cloud storage APIs webhook listeners and streaming data sources for third-party integration
- Analyze integration requirements to design connector architectures supporting real-time and batch multi-source data unification
Data Actions
- Identify data actions including flow triggers platform events and webhook callouts for activating insights in downstream systems
- Configure data action triggers including segment membership changes profile updates and calculated insight thresholds for automation
- Configure webhook integrations including endpoint configuration payload mapping and retry policies for external system activation
- Analyze data action requirements to design event-driven architectures connecting Data Cloud insights with operational workflows
7
Domain 7: Implementation
2 topics
Deployment Planning
- Identify implementation considerations including data volume estimation processing windows and org limits for Data Cloud deployment
- Configure sandbox environments including test data loading connector validation and segment testing for pre-production verification
- Configure deployment plans including phased data source onboarding identity resolution tuning and activation testing for go-live
- Analyze implementation requirements to design rollout strategies prioritizing high-value data sources and activation use cases
Performance Optimization
- Identify performance factors including data volume query complexity identity resolution processing and segment refresh times
- Configure performance monitoring including processing time dashboards error rate tracking and data freshness metrics for health
- Configure optimization strategies including data retention policies archive rules and query tuning for sustainable platform performance
- Analyze performance data to recommend scaling strategies data lifecycle policies and query optimization for long-term sustainability
8
Domain 8: Use Cases and Best Practices
2 topics
Industry Use Cases
- Identify Data Cloud use cases including single customer view personalization journey orchestration and advertising activation
- Configure retail use cases including customer 360 profiles loyalty program integration and personalized product recommendations
- Configure financial services use cases including client 360 next-best-action and regulatory compliance data management
- Analyze industry requirements to design Data Cloud solutions addressing vertical-specific data unification and activation needs
Best Practices
- Identify Data Cloud best practices including data hygiene ingestion patterns identity resolution tuning and activation strategies
- Configure data hygiene workflows including source validation enrichment rules and quality monitoring for clean unified profiles
- Configure documentation including data dictionaries lineage maps and governance policies for sustainable Data Cloud operations
- Analyze Data Cloud maturity to design roadmaps progressing from basic unification through advanced AI-driven activation stages
Scope
Included Topics
- Salesforce Certified Data Cloud Consultant exam topics.
Not Covered
- Custom Apex/LWC development.
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