Data 360 Consultant Study Guide
The CertifyForce Data 360 Consultant study guide covers the official Salesforce Data 360 Consultant exam outline in 22 units across all 6 exam sections, one unit per exam-guide topic. The exam itself has 60 scored questions plus 5 unscored, a 105-minute limit and a 70% passing score, and its largest section is Data Activations and Utilization at 20%. Every unit is verified against official Salesforce documentation, cites its sources, and links to the practice questions that test it. Last updated October 16, 2026.
Formerly Data Cloud Consultant. Validates designing and implementing Data 360 (formerly Data Cloud): solution positioning, setup and governance, ingestion and Zero-Copy, harmonization and unification, insights and AI, segmentation, and activation.
22 lessons · 6 exam sections · about 3 h of reading ·
Exam sections
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Every lesson's summary, exam expectations, key facts and self-check questions are free to read. The Data 360 Consultant pack unlocks the self-check answers, core concepts, exam traps and worked scenarios, reading progress, personalized “read next”, and unlimited practice exams.
Solution Positioning
14% of the exam- Data 360 terminology, data model and value~8 minThe core Data 360 vocabulary from data stream to activation, the Customer 360 Data Model terms (subject area, DMO, attribute, primary and foreign key), and how a consultant proves value with use-case KPIs, ROI math and consumption-based credit pricing.
- Data 360 as the foundation for AI~7 minWhy agents and models need unified, clean, real-time and governed data, how Data 360 grounds generative AI through RAG and search indexes, what the Einstein Trust Layer stores in Data 360, and the three ways AI Models (formerly Einstein Studio) delivers predictions.
- Choosing initial Data 360 use cases~8 minHow to pick a first Data 360 use case: start small instead of a big-bang launch, answer the requirement and data questions first, anchor on unifying customers, reserve real-time for problems that need it (and build its prerequisites), and choose ingestion or Zero Copy federation.
- Data ethics, consent and trust principles~7 minThe five Salesforce data ethics best practices (minimization, value exchange, sensitive data and bias, least privilege, careful partners), Salesforce's Ethical and Humane Use guiding principles for AI, and which Data 360 governance control answers each compliance requirement.
Data 360 Setup and Administration
13% of the exam- Permission sets and data space access~8 minWhat each standard Data 360 permission set (Data Cloud Architect, Activation Manager, Activation Specialist, User) can do, why to keep the standard sets, how to migrate assignments, how data spaces and per-space feature permissions scope access, and the org settings enrichments and external org connections need.
- Data governance: tags, policies and masking~8 minHow Data 360 turns governance requirements into configuration: tags and AI tag suggestions, tag propagation, allow and deny access policies at object, field and record level, Dynamic Data Masking methods, the ABAC setup steps (ending with deleting Allow All), and Platform Encryption key options.
- Sandboxes, data kits and deployment~7 minWhat a Data 360 sandbox copies (metadata, never data), how to enable it (including license match), what it costs, how to keep production activation targets safe, and how to deploy with DevOps data kits through change sets or the Salesforce CLI, including governance mergeback.
- Troubleshooting refreshes, consumption and lineage~7 minWhich Data 360 tool diagnoses which problem: data stream and DLO Refresh History, connector errors, problem record DLOs, missing-file alerts, identity resolution job statuses, query-time policy behaviour and unified lineage.
Data Source Connection and Ingestion
18% of the exam- Streaming and batch data transforms~7 minHow to choose between streaming data transforms, batch data transforms and data stream formula fields, how each one is built and constrained, and what decides incremental versus full runs and their credit cost.
- Data streams, connectors and ingestion settings~7 minWhich connector fits each source, the one-time choices on a data stream (category, primary key, event time), refresh modes and schedules per connector, Ingestion API schema and delete rules, and the settings that cut ingestion credits.
- Zero Copy, data shares and clean rooms~7 minZero Copy in both directions: query and file federation bring external data in (live or accelerated), data shares send Data 360 objects out to Snowflake, Databricks, BigQuery, Redshift or another Data 360 org, and clean rooms let two parties query each other's data without exposing raw records.
Harmonization and Unification
17% of the exam- Identity resolution: match and reconciliation rules~8 minHow identity resolution builds unified profiles: unification types, ruleset setup and IDs, match rules and methods, reconciliation rules, unified link objects, known versus anonymous profiles, scheduled versus real-time runs, and the levers that control credit use.
- Data mapping, DMOs, relationships and data graphs~8 minHow to model data in Data 360: mapping rules and automapping, required party mappings, key qualifiers, custom DMOs and their categories, relationship cardinality and limits, and designing standard, streaming and real-time data graphs.
Data Enhancements, Sharing, and Analysis
18% of the exam- Calculated, streaming and real-time insights~8 minHow to pick calculated, streaming or real-time insights for a metric, build them with Visual Builder or SQL (case-sensitive DMO names, TRY_CONVERT_CURRENCY, NOW and SECOND_ADD), and schedule, run, validate and history-track them.
- Querying Data 360 from apps, APIs and orgs~7 minWhich way to reach Data 360 data from outside it: Data Explorer and Query Editor, the SQL Query APIs (async paging, caching, workloadName), JDBC, Python and the Connect API for Apex, companion versus standard org connections, and data shares between Data 360 orgs.
- Data 360 reports, dashboards and Tableau~7 minStandard versus custom Data 360 reports, the fixed rules of calculated insight reports and their charts (dimensions, aggregatable and non-aggregatable measures, no details or formulas), mixing Data 360 and CRM reports on one dashboard, and when Tableau is the better tool.
- AI models, vector and hybrid search~7 minMatching customer scenarios to Data 360 AI tooling: AI Models sources and capabilities (regression, binary classification), where active predictions are used, and vector versus hybrid search indexes with their chunk and index objects and use cases.
Data Activations and Utilization
20% of the exam- Segmentation concepts: attributes, containers and population~8 minWhat segmentation is for and how the segment canvas thinks: Segment On, the attribute library, direct versus related attributes, containers and filter logic, population counts and preview, and building segments from natural language with Einstein segments or the Data 360 Marketing Agent.
- Segment types, publishing and limits~8 minHow to pick and run the right segment: standard, real-time, waterfall, dynamic and nested segments, standard versus rapid publish schedules, concurrency, segment and publish statuses, the Segment Membership DMO, and the limits and credit levers a consultant must design around.
- Activations: targets, membership and contact points~7 minHow a segment reaches a channel: activation targets, Unified Individual as activation membership, contact points per target and source priority order, full versus incremental refresh, waterfall subsegment activation, calculated insights and related attributes in the payload, and activation filters.
- Data actions, targets and enrichments~7 minHow to act on Data 360 data beyond segment activation: choosing between data actions, enrichments, data shares and clean rooms, then building data actions (targets, primary and related objects, event and action rules, permissions, limits) and related list and copy field enrichments.
- Data 360 in flows and orchestration~7 minFour ways Flow works with Data 360: Data Cloud-triggered flows that start from DMO changes, Get Records on a Data Cloud Object, data actions that reach Flow through platform events, and autolaunched flows that chain ingestion, identity resolution, insights and segmentation with Wait for Conditions.
Common questions about the Data 360 Consultant study guide
Is the Data 360 Consultant study guide free?
Partly. Every unit's summary and its "What the exam expects", "Key facts" and "Check yourself" sections are free to read without an account. The "Core concepts", "Exam traps" and "Worked scenario" sections, reading progress and unlimited timed mock exams come with the Data 360 Consultant pack (USD $19).
How current is the Data 360 Consultant study guide?
It is written to the current official Salesforce Data 360 Consultant exam outline, and each unit is checked against Salesforce documentation before it is published. The most recent update was October 16, 2026, and every unit shows its own last-updated date.
How does the study guide map to the official Data 360 Consultant exam guide?
There is one unit per topic in the official exam guide, grouped under its 6 weighted sections: Solution Positioning (14%), Data 360 Setup and Administration (13%), Data Source Connection and Ingestion (18%), Harmonization and Unification (17%), Data Enhancements, Sharing, and Analysis (18%), Data Activations and Utilization (20%). Each unit quotes the exam objective it covers word for word.
How do the practice questions link to the study guide?
Each unit lists the reviewed practice questions that test it (300 questions are linked across the guide), so you can read a topic and practice it in one click. After a practice exam, every missed question links back to the unit that teaches it.