CRM Analytics and Einstein Discovery Consultant Advanced Practice Exam: Hard Questions 2025

A global manufacturer ingests weekly CSV extracts into a CRM Analytics dataflow. The source system occasionally changes column names (for example, `Acct_ID` becomes `AccountId`) and sometimes adds new columns. The dataflow intermittently fails with schema mismatch errors, and the analytics team wants the load to be resilient without silently corrupting data. Which approach best balances resiliency and data quality?

A retail company maintains a "Customer 360" dataset built from Account, Contact, Orders, and Loyalty tables. They need to support both (1) highly interactive dashboards with row-level security and (2) data science exploration where analysts need a denormalized wide table with consistent grain. The current single dataset mixes order-level and customer-level attributes, causing double-counting and inconsistent aggregates. What is the best architecture in CRM Analytics to resolve this?

A dataset is built from two sources: Salesforce Opportunities (near real time) and a nightly ERP extract for bookings adjustments. Users complain that dashboard totals change unexpectedly during the day and sometimes show partial ERP adjustments. You need a design that provides consistent daily executive reporting while still allowing near-real-time operational views. Which solution is best?

A CRM Analytics dashboard includes a date range selector and several charts. A particular chart uses a comparison period (previous period) and a "Top N" list. After a recent update, the chart intermittently returns fewer than N items and the previous-period comparison appears misaligned when users switch between fiscal and calendar date contexts. What is the most likely root cause and best fix?

A dashboard is used by sales managers across regions. Requirements: (1) the same dashboard must automatically show only the viewer’s region; (2) a manager can optionally switch to view a peer region for comparison, but cannot see underlying row-level details outside their region; (3) the dashboard must remain performant. Which design best meets these requirements?

A service organization built a complex dashboard with 14 steps and heavy inter-step bindings. Users report sporadic "Too many queries" or timeouts when interacting quickly with selectors. You need to improve responsiveness without removing key analyses. Which change is most effective and aligned with CRM Analytics best practices?

A company wants an Einstein Discovery model to predict renewal likelihood. Their dataset includes an "Auto_Renewed" field that is populated only after the renewal process completes, and a "Renewal_Decision_Date" field that can occur after the prediction would be made. The initial model shows extremely high accuracy but performs poorly in production. What is the most likely issue and the best corrective action?

An Einstein Discovery model is built on Opportunities to recommend actions that increase win probability. Leadership wants the recommendations embedded in Salesforce so that sellers see a single recommended "next best action" with an explanation. Compliance requires that the recommendation never suggests actions that violate a policy (for example, discount above a threshold), even if the model believes it improves win rate. What is the best implementation approach?

After deploying an Einstein Discovery model, the business changes its sales process and introduces a new product line. Within weeks, prediction distributions shift significantly and accuracy drops for the new product line. The consultant must propose a monitoring and retraining strategy that minimizes disruption and supports auditability. What is the best recommendation?

A regulated financial services firm uses CRM Analytics with strict least-privilege requirements. They need to allow analysts to build dashboards on curated datasets but must prevent them from exporting row-level data or accessing sensitive fields (SSN, DOB). Additionally, executives should be able to view dashboards but never edit them. Which security design best meets these requirements?