Pearson Data-Cloud-Consultant New Attempt

Data Cloud handles an individual’s Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.

The other options are not correct descriptions of how Data Cloud handles an individual’s Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.

Requesting Data Deletion or Right to Be Forgotten

Data Deletion for Data Cloud

Use the Consent API with Data Cloud

Data and Identity in Data Cloud

 The error “Segment references too many data lake objects (DLOs)” occurs when a segment query exceeds the limit of 50 DLOs that can be referenced in a single query. This can happen when the segment has too many filters, nested segments, or exclusion criteria that involve different DLOs. To remedy this issue, the consultant can try the following troubleshooting tips:

Split the segment into smaller segments. The consultant can divide the segment into multiple segments that have fewer filters, nested segments, or exclusion criteria. This can reduce the number of DLOs that are referenced in each segment query and avoid the error. The consultant can then use the smaller segments as nested segments in a larger segment, or activate them separately.

Use calculated insights in order to reduce the complexity of the segmentation query. The consultant can create calculated insights that are derived from existing data using formulas. Calculated insights can simplify the segmentation query by replacing multiple filters or nested segments with a single attribute. For example, instead of using multiple filters to segment individuals based on their purchase history, the consultant can create a calculated insight that calculates the lifetime value of each individual and use that as a filter.

The other options are not troubleshooting tips that can help remedy this issue. Refining segmentation criteria to limit up to five custom data model objects (DMOs) is not a valid option, as the limit of 50 DLOs applies to both standard and custom DMOs. Spacing out the segment schedules to reduce DLO load is not a valid option, as the error is not related to the DLO load, but to the segment query complexity.

Troubleshoot Segment Errors

Create a Calculated Insight

Create a Segment in Data Cloud

The correct answer is A. Deactivate the segment. If a segment is no longer needed, it can be deactivated through Data Cloud and applies to all chosen targets. A deactivated segment no longer publishes, but it can be reactivated at any time1. This option allows the user to pause a segment activation with the intent of using that segment again.

The other options are incorrect for the following reasons:

B. Delete the segment. This option permanently removes the segment from Data Cloud and cannot be undone2. This option does not allow the user to use the segment again.

C. Skip the activation. This option skips the current activation cycle for the segment, but does not affect the future activation cycles3. This option does not pause the segment activation indefinitely.

D. Stop the publish schedule. This option stops the segment from publishing to the chosen targets, but does not deactivate the segment4. This option does not pause the segment activation completely.

1: Deactivated Segment article on Salesforce Help

2: Delete a Segment article on Salesforce Help

3: Skip an Activation article on Salesforce Help

4: Stop a Publish Schedule article on Salesforce Help

To address Northern Trail Outfitters' requirement of creating a segment with customers who have purchased in the last 24 hours, while ensuring the data is as up to date as possible, streaming insights is the most appropriate solution. Here's why:

Understanding Streaming Insights :Salesforce Data Cloud provides Streaming Insights , which enables near real-time data processing and segmentation. This feature allows businesses to capture and act on customer interactions or transactions almost instantly, making it ideal for time-sensitive use cases like identifying recent purchasers.

Why Not Other Options?

Option B (Einstein Segmentation Optimization) : Einstein Segmentation Optimization focuses on improving segment performance using AI but does not inherently provide near real-time data updates. It is more about refining existing segments rather than ensuring low-latency data availability.

Option C (Rapid Segments with a Publish Interval of 1 Hour) : Rapid Segments are faster than standard segments but still involve a delay due to the publish interval. A 1-hour interval would not meet the "as up to date as possible" requirement.

Option D (Standard Segment with a Publish Interval of 30 Minutes) : Standard segments are processed less frequently and typically involve longer delays. Even with a 30-minute interval, this option cannot match the near real-time capabilities of streaming insights.

How Streaming Insights Works :

Streaming Insights processes data from connected sources (e.g., CRM, external systems) in near real-time.

When a customer makes a purchase, the transaction data is ingested into Data Cloud and immediately available for segmentation.

The consultant can configure a segment rule to include only customers whose purchase timestamp falls within the last 24 hours.

Salesforce Documentation Reference :According to Salesforce's official Data Cloud documentation, Streaming Insights is designed for scenarios where timely data is critical. It ensures that segments reflect the latest customer behavior without significant delays, aligning perfectly with Northern Trail Outfitters' needs.