Salesforce Data 360 (Data Cloud) Consultant Practice Exam

A retailer wants to bring customer data from Salesforce CRM, an e-commerce platform, an email tool, and a mobile app into Data 360. Each system uses different customer identifiers. What is the first step the consultant should take?

1. Configure a data stream for each source system, map the data to the Data 360 data model, and define the ingestion schedule
2. Import all data into a single Salesforce custom object
3. Wait until every source system uses the same customer identifier before starting
4. Build a custom ETL pipeline outside of Data 360

A consultant has ingested customer data from five sources. Customers exist in multiple systems with different IDs — email in the CRM, loyalty number in the POS, device ID in the mobile app. How should the consultant configure identity resolution?

1. Choose a single identifier and delete records from systems that do not use it
2. Configure match rules using deterministic matching (email, phone, loyalty ID) and probabilistic matching (name/address similarity) to build unified individual profiles
3. Write a custom Apex class that matches records on a single field
4. Manually merge duplicate records one by one

A marketing team wants a segment of all customers who purchased in the last 90 days, opened at least three emails in the last 30 days, and have a predicted high lifetime value. What should the consultant use?

1. A custom SOQL query against the Data 360 data model
2. A Salesforce report filtered by these three criteria
3. Segment Builder with filters combining purchase behavior, email engagement, and a calculated insight for predicted lifetime value
4. An Excel spreadsheet exported from each source system and merged manually

A consultant has built segments and the marketing team wants to activate them to Marketing Cloud for email and to an ad platform for retargeting. How should the consultant configure this?

1. Share Data 360 login credentials with the marketing team so they can access segments directly
2. Build a custom API integration between Data 360 and each advertising platform
3. Configure activation targets for Marketing Cloud and the ad platform, mapping segment attributes to each platform’s required format
4. Export segment lists as CSV files and upload them to each platform manually

A company wants a metric that predicts customer churn probability based on purchase-frequency decline, rising support-case volume, and dropping engagement scores. What should the consultant configure?

1. An Einstein Analytics dashboard that displays churn indicators
2. A formula field on the Contact object in Sales Cloud
3. A batch Apex job that runs daily to calculate churn scores
4. A calculated insight in Data 360 that combines behavioral metrics from unified profiles into a churn-probability score

A healthcare company using Data 360 must handle patient data in compliance with HIPAA, and only authorized users should see protected health information. What governance measures should the consultant implement?

1. Encrypt all data and grant everyone access, since encryption is sufficient
2. Store patient data in a separate, disconnected system outside Data 360
3. Configure consent management, data access policies, and field-level restrictions so only authorized roles can view PHI, with audit logging enabled
4. Rely solely on Salesforce profile-based security with no additional Data 360 configuration

A consultant finds that identity resolution is creating too many false matches, merging different customers who share a first name and city. How should the consultant refine the configuration?

1. Switch to manual review of every potential match
2. Accept the false matches, since some inaccuracy is inevitable
3. Disable identity resolution entirely to prevent false matches
4. Tighten match rules by adding required fields (email or phone), raising confidence thresholds, and adding exclusion rules for common name combinations

A consultant must monitor ingestion health across 10 data streams. Several streams have intermittent failures the team discovers days later. What monitoring approach should the consultant implement?

1. Build a custom polling application that checks status via API every hour
2. Configure Data 360 monitoring and alerts that notify the team immediately when data-stream ingestion fails or is delayed
3. Check each data stream manually once a week
4. Assume data streams are working unless users report missing data

A consultant is mapping a retailer’s e-commerce data — orders, order line items, products, and customers — into the Data 360 data model. How should the consultant map it?

1. Store the raw source data as-is without mapping to the data model
2. Create custom Data Model Objects for every source table without using standard objects
3. Map source entities to standard Data Model Objects — Individual for customers, Sales Order for orders, Sales Order Product for line items — preserving relationships
4. Dump all data into a single Data Model Object with denormalized fields

A financial-services client wants to use unified profiles to personalize the website experience in real time when a customer visits. What Data 360 capability should the consultant configure?

1. A nightly data export from Data 360 to the website’s database
2. Manual profile lookup by customer-service agents when customers call
3. A static personalization engine that uses rules without customer data
4. Data 360 real-time data actions (or web SDK integration) that query the unified profile and trigger personalization when the customer is identified on the site