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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 | - Insights interpretation and recommendations - Model building and predictions |
| Topic 3: Dashboard and App Development | - Lens creation and dashboard design - Interactive filters and user experience optimization |
| Topic 4: Data Management and Preparation | - Data transformation and dataflows - Dataset creation and configuration in CRM Analytics |
| Topic 5: Security and Access | - App and dataset permissions - Row-level security and sharing rules |
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NEW QUESTION # 40
The CRM Analytics project team at Universal Containers is creating an app with dashboards, datasets, and lenses. The app has been shared with multiple users with Viewer, Editor, and/or Manager access.
One end user is unable to view the dashboard watchlist that was previously set up. They are receiving a
"Resource not found" error while trying to access the dashboard. The team confirms that the end user has Viewer access to the app but the project team is able to view the dashboard.
What is the reason for this error?
Answer: A
NEW QUESTION # 41
Acompany wants to create a timeline chart to visualize the evolution of its Closed Won opportunities.
What are the required parameters to build a lens that displays output similar to the image shown?
Answer: B
Explanation:
To create a timeline chart similar to the one shown, the following parameters are typically required:
* 1 Measure: This could be the count of Closed Won opportunities or any other relevant metric that needs to be tracked over time.
* 1 Grouping by a Date Field: This is essential to plot the timeline effectively. The date field would typically be the close date of the opportunities.
* Additional Groupings: Depending on the complexity and the detail needed, additional groupings can be added. For example, grouping by region or product line can provide more insights into the timeline. If trellis is used, it allows for the creation of multiple smaller charts within the main chart, each representing a slice of data based on the additional groupings.
This setup helps visualize the evolution of Closed Won opportunities over time, making it easy to spot trends, seasonal patterns, or other relevant insights.
NEW QUESTION # 42
A consultant runs the sharing inheritance coverage assessment for the Opportunity object and finds that some records exceed 400 sharing descriptors.
What should the consultant do?
Answer: A
Explanation:
When a record exceeds 400 sharing descriptors, it can cause performance issues or sharing rule complications in CRM Analytics. In such cases, the recommended solution is to usesecurity predicates, which allow fine- tuned control over which data is visible to users based on their sharing rules and permissions. Security predicates reduce the number of sharing descriptors by enforcing security at the dataset level rather than relying solely on record-sharing mechanisms.
Increasing the sharing descriptor limit is not an available option, and Salesforce Support does not typically increase this limit, making the use of security predicates the best approach.
NEW QUESTION # 43
What is the purpose of the CRM Analytics Dashboard Inspector?
Answer: C
Explanation:
The CRM Analytics Dashboard Inspector is a powerful tool used to troubleshoot and optimize dashboards. Its primary function is to display the underlying SAQL (Salesforce Analytics Query Language) query executed for each widget. It helps users see the final query that is run and the corresponding results. This feature allows CRM Analytics consultants and developers to diagnose issues, optimize performance, and understand how data is being processed in the dashboard.
While the Inspector helps view execution times and identify bottlenecks, it does not automatically resolve performance issues (which is why option B is incorrect). It simply provides visibility into query performance and execution details, allowing the user to make manual optimizations.
NEW QUESTION # 44
The sales team at Cloud Kicks is requesting that datasets for their dashboards be refreshed every hour. The CRM Analytics consultant investigates if this is possible and finds that the dashboards use five datasets created from two recipes. The first recipe takes 43 minutes to run and the second recipe takes 25 minutes to run.
Which consideration should the consultant keep in mind?
Answer: A
Explanation:
In CRM Analytics, recipes are used to prepare and combine data for datasets. The total duration of the recipe runtime is an important consideration when scheduling dataset refreshes. In this case, the combined runtime for both recipes (43 minutes + 25 minutes = 68 minutes) exceeds 1 hour. Since dataset refreshes cannot be scheduled more frequently than the total recipe runtime, it would beimpossible to refresh the datasets every hour. This limitation must be considered when managing dataset refresh schedules.
Reference: Recipe runtime limits and considerations for scheduling refreshes are discussed in the CRM Analytics documentation related to recipes and dataflow optimizations.
NEW QUESTION # 45
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