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CRM Analytics And Einstein Discovery Consultant Free Sample Questions

12 free sample questions120 in the full practice test

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Analytics-Con-201 Sample Questions

  1. Question 1

    A consultant is designing a dataset for a global sales team. The requirement states that regional managers should only see data for their specific region, while the VP of Sales must see all data. The Salesforce Org uses a Role Hierarchy where the VP is at the top, but the regional managers are in a custom 'Region' object related to the User object, not strictly in the standard Role Hierarchy. Which security implementation strategy effectively meets this requirement in CRM Analytics?

    Answer and explanation

    Correct answer: C

    Since the security requirement is based on a custom 'Region' object relationship rather than the standard Salesforce Role Hierarchy, standard inheritance won't work directly. The best approach is to flatten the relevant hierarchy or attributes into the dataset during data prep and then use a security predicate (e.g., 'Region' == '$User.Region__c' || 'VP_Flag' == true) to control visibility.

  2. Question 2

    A Universal Containers consultant has created an Einstein Discovery story to minimize customer churn. Upon reviewing the model metrics, the consultant notices that the 'Region' variable has a very high correlation with 'Churn', but the business team insists that Region itself does not cause churn, but rather the specific 'Support Team' assigned to that region. What feature should the consultant use to investigate if 'Region' is acting as a proxy for 'Support Team'?

    Answer and explanation

    Correct answer: B

    Multicollinearity occurs when two or more independent variables are highly correlated (e.g., Region and Support Team, if one team covers exactly one region). Einstein Discovery flags this because it makes it difficult to isolate the effect of each variable. If Region is a proxy for Support Team, they will likely be flagged as collinear.

  3. Question 3

    A consultant is tasked with creating a dashboard that allows users to toggle the measure displayed in a chart between 'Total Amount', 'Avg Amount', and 'Record Count'. The consultant decides to use a Static Step for the toggle selector. Which Interaction (Binding) syntax should be used in the chart's JSON to dynamically replace the measure based on the user's selection?

    Answer and explanation

    Correct answer: A

    To dynamically replace a measure (which consists of an aggregation function and a field, like ['sum', 'Amount']), you need to project the selection as an object or array of strings that the widget query can understand. The 'column' function is appropriate here to retrieve the selected values, and '.asObject()' formats it correctly for the JSON 'measures' property.

  4. Question 4

    A company requires a complex data transformation that involves joining five different datasets, performing three levels of aggregation, and calculating a sliding window average for sales data over the last 12 months. Which data preparation tool in CRM Analytics is most suitable for this requirement?

    Answer and explanation

    Correct answer: B

    Data Prep Recipes are the modern, recommended tool for complex transformations. Unlike Dataflows, Recipes natively support complex window functions (like sliding averages), multi-level aggregations, and provide a visual interface for joining multiple datasets with preview capabilities.

  5. Question 5

    True or False: In CRM Analytics, when you use the 'Inherit sharing from Salesforce' option on a dataset created from the Opportunity object, it will automatically respect Manual Sharing rules applied to individual Opportunity records.

    Answer and explanation

    Correct answer: B

    CRM Analytics security inheritance supports the Role Hierarchy and Sharing Rules, but it does NOT support Manual Sharing or Apex-managed sharing. For these cases, a security predicate must be used.

  6. Question 6

    A consultant is analyzing a 'Maximize Margin' story in Einstein Discovery. The 'Why it Happened' chart for a specific high-margin transaction shows a significant positive contribution from the 'Discount' field being 'Low'. However, the 'Actionable Insights' do not suggest changing the discount. What is the most likely reason for this omission?

    Answer and explanation

    Correct answer: A

    Einstein Discovery only generates suggestions (Actionable Insights) for variables that are explicitly flagged as 'Actionable' during the story setup. Even if a variable is highly predictive, it won't appear in recommendations if the system believes the user cannot control it.