Salesforce Certified Data Cloud Consultant Practice Exam

The Salesforce Certified Data Cloud Consultant certification validates your expertise in designing, implementing, and managing data solutions within the Salesforce Data Cloud. 

Who should consider this exam:

• Salesforce administrators and consultants seeking to specialize in data cloud solutions.
• Data analysts and architects looking to expand their knowledge of Salesforce data management.
• Individuals seeking a career focused on data management and analytics within Salesforce environments.

Key Roles and Responsibilities:

• Evaluate data needs and requirements: Analyze business needs and recommend appropriate data solutions using the Salesforce Data Cloud.
• Design and architect data solutions: Design and architect data solutions that leverage various data cloud components, including Data Integration, Einstein Analytics, and Tableau CRM.
• Implement data solutions: Configure and implement data pipelines, manage data quality, and ensure data governance.
• Optimize and monitor data solutions: Monitor data quality and performance, optimize data pipelines, and troubleshoot issues.
• Communicate and collaborate with stakeholders: Collaborate effectively with business stakeholders, technical teams, and data scientists to ensure successful data solution implementation.

Exam Details:

• Format: Multiple-choice questions and case studies
• Time Limit: 105 minutes
• Languages: English
  
• Passing Score: 62%

Course Outline

The Salesforce Data Cloud Consultant exam measures a candidate’s knowledge and skills related to the following topics - 

Domain 1 - Describe Solution Overview (18%)

• Learning about Data Cloud’s function, key terminology, and business value.
• Learning to Identify typical use cases for Data Cloud.
• Learning to Articulate the Data Cloud lifecycle and its dependencies..
• Learning and apply the principles of data ethics.

Domain 2 - Describe Data Cloud Setup and Administration (12%)

• Learning and apply Data Cloud permissions, permission sets, and org-wide settings.
• Learning and configure the available data stream types and data bundles.
• Learning to identify use cases for data spaces and create data spaces based on requirements.
• Learning to manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits.
• Learning to diagnose and explore data using Data Explorer, Profile Explorer, and APIs.

Domain 3 - Describe Data Ingestion and Modeling (20%)

• Learning to identify the different transformation capabilities within Data Cloud.
• Learning about processes and considerations for data ingestion from different sources into Data Cloud.
• Learning to define, map, and model data using best practices and aligning to requirements for identity resolution.
• Learning to use available tools to inspect and validate ingested and modeled data.

Domain 4 - Describe Identity Resolution (14%)

• Learning about matching and how its rule sets are applied.
• Learning to reconcile data and describe how its rule sets are applied.
• Learning to describe the results of identify resolution and use cases.

Domain 5 - Describe Segmentation and Insights (18%)

• Learning basic concepts of segmentation and use cases.
• Learning to identify scenarios for analyzing segment membership.
• Learning to configure, refine, and maintain segments within Data Cloud.
• Learning to identify and differentiate between calculated and streaming insights.

Domain 6 - Describe Act on Data (18%)

• Learning about activations and their basic use cases.
• Learning to use attributes and related attributes.
• Learning to identify and analyze timing dependencies affecting the Data Cloud lifecycle.
• Learning to troubleshoot common problems with activations including accepted/rejected counts, errors, and not seeing related attributes.
• Learning to use data actions and identify their requirements and intended use cases.