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Cert++

Resource Pack
·Study Checklist

Data Cloud Consultant

The Salesforce Certified Data Cloud Consultant credential is one of the more technically demanding consultant exams on the platform. It goes well beyond knowing what Data Cloud does -- you need to understand the full pipeline from raw ingestion through semantic mapping, identity resolution, segmentation, and activation. If you have been working hands-on with Data Cloud for a few months, you are in good shape to start studying. If you are coming from a Marketing Cloud or CRM Analytics background, expect to spend extra time on the data model and identity resolution topics, which are unlike anything else in the Salesforce ecosystem.

4-Step Path to Passing

  1. 1
    Complete the
    Unlock Your Data with Data Cloud Trailmix
  2. 2
    Look at the
    Study Checklist
    Every concept you need to know for your exam, available for free to check off as you learn.
  3. 3
    Attempt
    Practice Exams
  4. 4
    Schedule Your Exam

Core Resources

Exam Overview

Questions

65

60 scored + 5 unscored

Duration

105 min

1 hour 45 minutes

To Pass

65%

Minimum Score

Question Format

The exam tests your ability to configure and troubleshoot the full Data Cloud pipeline: connecting data sources, modeling and transforming data, resolving identity across profiles, building and activating segments, and using data actions and enrichments.

Scored

92%

60questions

Unscored

8%

5questions

Exam Details

Pricing

$200 registration · $100 retake

Delivery

Online proctored or at a testing center

Experience

Prerequisites

No prerequisites required

Exam Topics

Each topic section shows the topic weight, learning objectives, and links to study resources.

Data Cloud Overview18%

Data Cloud platform architecture and terminology, core data flow stages, typical use cases across Sales, Service, and Marketing, dependencies on connected orgs, and data ethics principles including consent, suppression, and right-to-be-forgotten.

  • Describe Data Cloud's function, key terminology, and business value.
  • Articulate how Data Cloud works and its dependencies.
  • Identify typical use cases for Data Cloud.
  • Describe and apply the principles of data ethics.

Resources

Data Cloud Setup and Administration12%

Permission sets specific to Data Cloud, data spaces for multi-brand or multi-region isolation, data bundles and kits for packaged configuration, Data Explorer and Profile Explorer for diagnostics, reports and dashboards for monitoring, and Salesforce Flow integration.

  • Apply Data Cloud permissions, permission sets, and org-wide settings.
  • Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits.
  • Diagnose and explore data using Data Explorer, Profile Explorer, and APIs.
  • Describe and configure the available data stream types and data bundles.
  • Identify use cases for data spaces and create data spaces based on requirements.

Resources

Data Ingestion and Modeling20%

Connector types and refresh modes, Data Streams vs. Data Lake Objects vs. Data Model Objects, streaming and batch data transforms, formula fields in DMOs, mapping source fields to canonical model entities (Individual, Contact Point Email, Engagement), and tools for inspecting and validating ingested data.

  • 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.

Resources

Identity Resolution14%

Fuzzy vs. exact matching rules, reconciliation rule types and priority order (last updated, most frequent, source priority), Unified Individual and Unified Contact Point output objects, multi-source merge scenarios, and validating unified profile output.

  • Describe matching and how its rule sets are applied.
  • Reconcile data and describe how its rule sets are applied.
  • Describe the results of identity resolution and use cases.

Resources

Segmentation and Insights18%

Segment creation and filtering, batch vs. streaming segments, related attributes and nested segments, segment exclusions, calculated insights using SAQL-like expressions, streaming insights for near-real-time event processing, data graphs for query optimization, and SQL-based insights.

  • Identify and differentiate between calculated and streaming insights.
  • Define basic concepts of segmentation and use cases.
  • Identify scenarios for analyzing segment membership.
  • Configure, refine, and maintain segments within Data Cloud.

Resources

Act on Data18%

Activation targets and publishing to external destinations (Marketing Cloud, advertising platforms, CRM), data actions via Salesforce Flow and webhooks, timing dependencies and refresh cadence, troubleshooting accepted vs. rejected activation records, CRM enrichments, and Data Cloud-powered Agentforce.

  • Describe and configure activation targets and associated use cases.
  • Define activations and their basic use cases.
  • Configure and troubleshoot data actions.
  • 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 blank field values.

Resources

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