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Free ANC301 Exam Braindumps (page: 14)

Page 13 of 30
PDF with 242 Questions

Universal Containers plans to upload target data from an external tool to CRM Analytics so it can calculate the sales team target attainments.
The target data changes every month, so the datasets need to be updated on a monthly basis. The target data is a CSV file that contains the Salesforce ID of the sales rep, the target amount, and the month of the target. For each sales rep, the file contains a target for every month of the current year as well as all previous years.
Based on this information, which operation should a consultant use with the Analytics External Data API to upload the file?

  1. Overwrite
  2. Update
  3. Append

Answer(s): A

Explanation:

For uploading target data that changes on a monthly basis and includes historical data (previous years' targets), the appropriate operation is "Overwrite." This ensures that each time the CSV file is uploaded, the existing data in the dataset is replaced with the new data. This is critical because the target data includes both current and historical data, and using "Overwrite" will update the entire dataset while maintaining historical accuracy.
"Append" would add new data without replacing the old records, leading to duplication, and "Update" is not suitable for completely replacing data in this context.


Reference:

The usage of the "Overwrite" operation for updating datasets with changing data is covered in the Analytics External Data API documentation, as well as in the Wave Analytics Explorer module.



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?

  1. Analytics Dataset XMD was NOT included as part of the deployment package,
  2. The recipe that generated the dataset also needs to be included as part of the package.
  3. Analytics Dashboard XMD was NOT included as part of the deployment package.

Answer(s): A

Explanation:

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.


Reference:

Detailed information on XMD files and their role in formatting is covered in the CRM Analytics deployment and customization documentation.



Cloud Kicks needs a CRM Analytics consultant to install the Appointment Analytics App. After installation, they realize the wrong field was picked and the app did not have access to a newly created field that should be used instead of the old one.
What is the first step the consultant should take to prevent erroneous dataset/dashboard creation?

  1. Cancel running installations from Setup
  2. Stop the recipe from running in Data Manager.
  3. Update the app with the new field after installation.

Answer(s): B

Explanation:

If the wrong field is selected in the initial setup of an app or dataset, it is important to stop any data processing activities (like recipe executions) to prevent erroneous data from being loaded into datasets and dashboards. In this case, stopping the recipe from running in Data Manager is the correct first step. Once the recipe is stopped, the consultant can update the field selection or make other necessary corrections before restarting the process.


Reference:

The Data Manager section in CRM Analytics outlines how recipes and data flows are managed, including how to stop or pause recipes.



What is a benefit of introducing a second local connector?

  1. Better maintenance by having a connector per recipe
  2. Better deployment management between sandboxes and production environment
  3. Better performance by syncing data according to the refresh necessities

Answer(s): C

Explanation:

Introducing a second local connector in CRM Analytics can improve performance by enabling more granular control over data syncs. By having a separate connector, different datasets or recipes can be synchronized independently based on specific refresh needs, reducing load and improving overall performance. This approach helps optimize data flow operations, especially in large-scale deployments with varying data refresh requirements.


Reference:

Best practices for managing connectors and optimizing data sync performance can be found in the CRM Analytics performance optimization guides.






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