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Salesforce ANC-301 Exam Questions
- Salesforce Consultant Certifications
- Salesforce CRM Analytics and Einstein Discovery Consultant Certifications
- Topic 1: Overview of User Access on the Tableau CRM Platform/ Creating Tableau CRM Permission Sets
- Topic 2: Establishing Your Users and Development Process/ Discovery and Planning
- Topic 3: Preparing Datasets with Recipes with Data Prep/ Overview of the Dataflow Process
- Topic 4: Running, Monitoring, and Scheduling a Dataflow/ Loading External CSV Data
- Topic 5: Overriding Security for Implementation and Testing/ Implementing Ownership-Based Row-Level Security
- Topic 6: Adding Quick Action Menus for Records in Tableau CRM/ Overview of Extended Metadata (XMD)
- Topic 7: Optimizing Dashboards for a Mobile Device/ Dashboard Templates and Mobile Dashboards
- Topic 8: Implementing Team-Based Row-Level Security/ Assigning Licenses and Permission Sets to Users
- Topic 9: Understanding Filters in Lenses and Dashboards/ Creating and Sharing Tableau CRM Apps
- Topic 10: Overview of Tableau CRM Dashboard Templates/ Implementing Role-Based Row-Level Security
- Topic 11: Salesforce Analytics Query Language (SAQL)/ Building a Dashboard Using a Template
- Topic 12: Overview of Using Predicate Filters/ SAQL Queries in a Tableau CRM Dashboard
Free Salesforce ANC-301 Exam Actual Questions
Note: Premium Questions for ANC-301 were last updated On Sep. 09, 2025 (see below)
Universal Containers (UC) builds three Einstein Discovery models in Salesforce to predict and maximize its revenue per customer. The models are for every region UC has a business: EMEA, AMER, and APAC.
How should a consultant help UC deploy the three Einstein models to Salesforce?
In deploying Einstein Discovery models that are tailored to different regions (EMEA, AMER, and APAC), the best approach is to segment the account data by region and apply the specific model designed for each segment. This method ensures the following:
Relevance and Accuracy: Each model can be specialized to understand and predict based on regional dynamics, which may differ significantly across geographies in terms of market behavior, customer preferences, and economic conditions.
Efficiency: Deploying region-specific models avoids the dilution of predictive power that might occur if a single model were used across all regions, which could lead to less accurate predictions.
Scalability: This approach is scalable as UC can further refine each model as more regional data becomes available or as regional market conditions evolve.
A CRM Analytics consultant at Cloud Kicks is trying to upload data using an External Data API and the CSV file with the data was uploaded successfully. Upon analyzing the data using a lens, they find
they are unable to perform any mathematical operations as all the data and fields are treated as dimensions.
What is causing the problem?
CRM Analytics team plans to enable data sync.
Which limit specific to data syne should the team consider before enabling the feature because it may impact existing jobs?
In CRM Analytics, when planning to enable data sync, one of the critical considerations is the limit on the number of objects that can be enabled for data sync. This limit is essential because it determines how many different Salesforce objects (like Accounts, Opportunities, etc.) can be synchronized concurrently. Exceeding this limit could impact the performance of existing sync jobs or prevent new sync jobs from being configured.
Key points to consider include:
Performance Impact: Syncing too many objects simultaneously can lead to increased load times and potential delays in data availability, impacting users' ability to access up-to-date information.
Resource Allocation: CRM Analytics allocates resources based on the number of objects being synchronized, and there are practical limits to these resources to ensure stable and efficient operation.
For a more detailed understanding and to manage these limits effectively, Salesforce provides documentation and guidelines within the CRM Analytics resources, which can be further explored in the Trailhead modules specifically focusing on data management and synchronization practices.
A CRM Analytics consultant is updating an existing recipe.
They are looking to add a few additional fields onto the Account dataset. One of the fields to be added is a multi-select picklist field that needs to be shown as text on the dashboard.
What should the consultant do to accomplish this?
A CRM Analytics administrator is working on deploying a dashboard and a dataset from a developer sandbox to a full sandbox. They have deployed the dataset via change set and manually copy-pasted the dashboard JSON into the target org. However, they notice that the conditional formatting and the widget-specific number formats have been lost in the target environment.
What is causing this issue?
When deploying a dataset and dashboard between environments in CRM Analytics, it's essential to include the Extended Metadata (XMD) file, which controls aspects such as conditional formatting and number formatting. In this case, the administrator manually copied the dashboard JSON but did not deploy the Analytics Dataset XMD, which leads to the loss of conditional formatting and widget-specific number formats in the target environment. Including the XMD ensures that all formatting and metadata are transferred correctly.
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