The Salesforce Data Cloud Consultant exam preparation guide is designed to provide candidates with necessary information about the Data Cloud Consultant exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the Salesforce Certified Data Cloud Consultant exam.
It is recommended for all the candidates to refer the Data Cloud Consultant objectives and sample questions provided in this preparation guide. The Salesforce Data Cloud Consultant certification is mainly targeted to the candidates who want to build their career in Salesforce Consultant domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual Salesforce Data Cloud Consultant exam.
Salesforce Data Cloud Consultant Exam Summary:
| Exam Name | Salesforce Data Cloud Consultant |
| Exam Code | Data Cloud Consultant |
| Exam Price |
Registration fee: USD 200 Retake fee: USD 100 |
| Duration | 105 minutes |
| Number of Questions | 60 |
| Passing Score | 62% |
| Recommended Training / Books |
Unlock Your Data with Data Cloud Cert Prep: Salesforce Certified Data Cloud Consultant Discover Salesforce Data Cloud Fundamentals (SDC101) |
| Schedule Exam | Kryterion Webassessor |
| Sample Questions | Salesforce Data Cloud Consultant Sample Questions |
| Recommended Practice | Salesforce Certified Data Cloud Consultant Practice Test |
Salesforce Data Cloud Consultant Syllabus:
| Section | Objectives | Weight |
|---|---|---|
| Data cloud Overview |
- Describe Data Cloud’s function, key terminology, and business value. - Identify typical use cases for Data Cloud. - Articulate how Data Cloud works and its dependencies. - Describe and apply the principles of data ethics. |
18% |
| Data Cloud Setup and Administration |
- Apply Data Cloud permissions, permission sets, and org-wide settings. - Describe and configure the available data stream types and data bundles. - Identify use cases for data spaces and create data spaces based on requirements. - Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits. - Diagnose and explore data using Data Explorer, Profile Explorer, and APIs. |
12% |
| Data Ingestion and Modeling |
- Identify the different transformation capabilities within Data Cloud. - Describe processes and considerations for data ingestion from different sources into Data Cloud. - Define, map, and model data using best practices and aligning to requirements for identity resolution. - Use available tools to inspect and validate ingested and modeled data. |
20% |
| Identity Resolution |
- Describe matching and how its rule sets are applied. - Reconcile data and describe how its rule sets are applied. - Describe the results of identify resolution and use cases. |
14% |
| Segmentation and Insights |
- Define basic concepts of segmentation and use cases. - Identify scenarios for analyzing segment membership. - Configure, refine, and maintain segments within Data Cloud. - Identify and differentiate between calculated and streaming insights. |
18% |
| Act on Data |
- Define activations and their basic use cases. - Use attributes and related attributes. - Identify and analyze timing dependencies affecting the Data Cloud lifecycle. - Troubleshoot common problems with activations including accepted/rejected counts, errors, and not seeing related attributes. - Use data actions and identify their requirements and intended use cases. |
18% |