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| Section | Objectives |
|---|---|
| Topic 1: Data Integration and Connectivity | - Connecting external data sources - Data synchronization and refresh strategies |
| Topic 2: Einstein Discovery | - Model building and predictions - Insights interpretation and recommendations |
| Topic 3: Security and Access | - Row-level security and sharing rules - App and dataset permissions |
| Topic 4: Data Management and Preparation | - Data transformation and dataflows - Dataset creation and configuration in CRM Analytics |
| Topic 5: Dashboard and App Development | - Lens creation and dashboard design - Interactive filters and user experience optimization |
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NEW QUESTION # 111
A user is able to access the dashboards, lenses, and datasets of a particular app but is unable to change the name of the specific app.
What is causing the issue?
Answer: A
Explanation:
In CRM Analytics, the ability to modify the name of an app or make other significant changes typically requires Manager access. This level of access is distinct from Editor or Viewer permissions, which may allow for modifications to contents within the app but not to the app's core properties like its name. Here's the reasoning:
* Access Restrictions: Manager access is specifically designed to control structural changes within the app, including renaming the app, which is considered a higher privilege operation.
* Role-Based Access Control: This ensures that only users with the necessary permissions can make significant changes, protecting the integrity and configuration of the app.
Ensuring users have the appropriate level of access based on their responsibilities is a fundamental aspect of managing security and functionality in CRM Analytics.
NEW QUESTION # 112
The CRM Analytics consultant at Universal Containers has set data syncs and recipe runs back to back.
However, they notice that the data syncs and recipe run jobs fail repeatedly. Upon investigation, they realize the data syncs and recipes are tightly coupled which leads to too many runs being queued and eventually being canceled.
How should the consultant resolve this issue?
Answer: B
NEW QUESTION # 113
A CRM Analytics consultant has prepared a CSV file to be uploaded to CRM Analytics. By mistake, one of the column headers is modified as random non-alphanumeric characters "* & **( & *(%", which went unnoticed prior to uploading the file.
What is the expected behavior of the uploaded CSV column?
Answer: C
Explanation:
When uploading CSV files into CRM Analytics, column headers must follow certain formatting rules.
Headers containing non-alphanumeric characters, such as " & **( & (%", will automatically be adjusted.
Specifically, if the column header starts with non-alphanumeric characters or contains such characters, CRM Analytics will prefix the header with "X" to ensure compatibility with internal naming conventions. This behavior ensures that the column can be referenced in the platform without causing errors or conflicts.
Reference: You can find the CSV upload rules, including naming conventions and auto-formatting behaviors, outlined in theSalesforce CRM Analyticsdocumentation provided during training, particularly under the module "Wave Analytics Explorer."
NEW QUESTION # 114
Cloud Kicks (CK) has a dashboard in CRM Analytics with forecasting data. One widget is a compare table using the timeseries function showing the quarterly forecast. However, CK is interested in enhancing the dashboard with a weekly forecast per customer.
How should CK achieve this?
Answer: B
Explanation:
To create a weekly forecast per customer, anSAQL (Salesforce Analytics Query Language)query can be used.
The timeseries function generates forecast data based on a specified date range. In this case, the forecast is customer-specific, meaning the partition should be based onAccount Nameto ensure that the forecast is generated for each customer. The date column (Date Cols) should be set to Y-M-W to aggregate the forecast data on a weekly basis.
NEW QUESTION # 115
Universal Containers' CRM Analytics team is building a dashboard with two widgets, and the queries use different datasets.
1. List widget associated to the query "Type_2" and grouped by the dimension "Type" (multi-selection)
2. Donut chart widget associated to the query "Query_pie_3" and grouped by the dimension "Type" The team wants any selection in the List widget to filter the Donut chart and vice versa. Users should be able to choose more than one Type (multi-selection).
What is the recommended way to accomplish the required filtering?
Answer: B
NEW QUESTION # 116
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