Get Salesforce Data-Cloud-Consultant Exam Dumps

Answer : B

Identity resolution is the process of creating unified profiles of individuals by matching and merging data from different sources. When there is conflicting information in the data model, such as different names, addresses, or phone numbers for the same person, identity resolution leverages reconciliation rules to select the most accurate and complete attributes for the unified profile. Reconciliation rules are configurable rules that define how to resolve conflicts based on criteria such as recency, frequency, source priority, or completeness. For example, a reconciliation rule can specify that the most recent name or the most frequent phone number should be selected for the unified profile. Reconciliation rules can be applied at the attribute level or the contact point level.Reference:Identity Resolution,Reconciliation Rules,Salesforce Data Cloud Exam Questions

Answer : C, D

: A customer who wants to view the last time each segment was published within their Data Cloud org can use the dashboard and report features to achieve this requirement. A dashboard is a visual representation of data that can show key metrics, trends, and comparisons. A report is a tabular or matrix view of data that can show details, summaries, and calculations. Both dashboard and report features allow the user to create, customize, and share data views based on their needs and preferences. To view the last time each segment was published, the user can create a dashboard or a report that shows the segment name, the publish date, and the publish status fields from the segment object. The user can also filter, sort, group, or chart the data by these fields to get more insights and analysis. The user can also schedule, refresh, or export the dashboard or report data as needed.Reference:Dashboards,Reports

Answer : C

The solution that provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis is the Marketing Cloud Data extension Data Stream. The Marketing Cloud Data extension Data Stream is a feature that allows customers to stream data from Marketing Cloud data extensions to Data Cloud data spaces. Customers can select which data extensions they want to stream, and Data Cloud will automatically create and update the corresponding data model objects (DMOs) in the data space. Customers can also map the data extension fields to the DMO attributes using a user interface or an API. The Marketing Cloud Data extension Data Stream can help customers ingest subscriber profile attributes and other data from Marketing Cloud into Data Cloud without writing any code or setting up any complex integrations.

The other options are not solutions that provide an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. Automation Studio and Profile file API are tools that can be used to export data from Marketing Cloud to external systems, but they require customers to write scripts, configure file transfers, and schedule automations. Marketing Cloud Connect API is an API that can be used to access data from Marketing Cloud in other Salesforce solutions, such as Sales Cloud or Service Cloud, but it does not support streaming data to Data Cloud. Email Studio Starter Data Bundle is a data kit that contains sample data and segments for Email Studio, but it does not contain subscriber profile attributes or stream data to Data Cloud.

Marketing Cloud Data Extension Data Stream

Data Cloud Data Ingestion

[Marketing Cloud Data Extension Data Stream API]

[Marketing Cloud Connect API]

[Email Studio Starter Data Bundle]

Answer : B, C

: When ingesting data from an Amazon S3 bucket, the consultant should configure the following options:

The refresh mode should be set to ''Upsert'', which means that new and updated records will be added or updated in Data Cloud, while existing records will be preserved. This ensures that the data is always up to date and consistent with the source.

The filename should contain a wildcard to accommodate the timestamp, which means that the file name pattern should include a variable part that matches the timestamp format. For example, if the file name isstore_transactions_2023-12-18.csv, the wildcard could bestore_transactions_*.csv. This ensures that the ingestion process can identify and process the correct file every day.

The other options are not necessary or relevant for this scenario:

Deletion of old files is a feature of the Amazon S3 bucket, not the Data Cloud ingestion process. Data Cloud does not delete any files from the source, nor does it require the source files to be deleted after ingestion.

Full Refresh is a refresh mode that deletes all existing records in Data Cloud and replaces them with the records from the source file. This is not suitable for this scenario, as it would result in data loss and inconsistency, especially if the source file only contains the summary of the last 24 hours of transactions.Reference:Ingest Data from Amazon S3,Refresh Modes

Answer : D

The segment membership data model object is a Data Cloud component that allows for analyzing individuals who have been in a segment within a certain time period. The segment membership data model object is a table that stores the information about which individuals belong to which segments and when they were added or removed from the segments. This object can be used to create calculated insights, such as segment size, segment duration, segment overlap, or segment retention, that can help measure the effectiveness of segmentation and activation strategies. The segment membership data model object can also be used to create nested segments or segment exclusions based on the segment membership criteria, such as segment name, segment type, or segment date range. The other options are not correct because they are not Data Cloud components that allow for analyzing individuals who have been in a segment within the last 2 years. Nested segments and segment exclusions are features that allow for creating more complex segments based on existing segments, but they do not provide the historical data about segment membership. Calculated insights are custom metrics or measures that are derived from data model objects or data lake objects, but they do not store the segment membership information by themselves.Reference:Segment Membership Data Model Object,Create a Calculated Insight,Create a Nested Segment