QUESTION: 69

Every day, Northern Trail Outfitters uploads a summary of the last 24 hours of store transactions to a new file in an Amazon S3
bucket, and files older than seven days are automatically deleted. Each file contains a timestamp in a standardized naming convention.
Which two options should a consultant configure when ingesting this data stream? Choose 2 answers

Ensure that deletion of old files is enabled.
Ensure the refresh mode is set to "Upsert".
Ensure the filename contains a wildcard to a accommodate the timestamp.
Ensure the refresh mode is set to "Full Refresh.''

Answer(s): B,C

Explanation:

: 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 is store_transactions_2023-12-18.csv, the wildcard could be store_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

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QUESTION: 70

Which solution provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis?

Automation Studio and Profile file API
Marketing Cloud Connect API
Marketing Cloud Data extension Data Stream
Email Studio Starter Data Bundle

Answer(s): C

Explanation:

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.

Reference:

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]

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QUESTION: 71

A customer has a requirement to be able to view the last time each segment was published within their Data Cloud org.
Which two features should the consultant recommend to best address this requirement?

Choose 2 answers

Profile Explorer
Calculated insight
Dashboard
Report

Answer(s): C,D

Explanation:

: 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

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QUESTION: 72

Which information is provided in a .csv file when activating to Amazon S3?

An audit log showing the user who activated the segment and when it was activated
The activated data payload
The metadata regarding the segment definition
The manifest of origin sources within Data Cloud

Answer(s): B

Explanation:

When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to the activation target, which in this case is an Amazon S3 bucket. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab.

Reference:

Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation

Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]

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Free Data-Cloud-Consultant Exam Braindumps (page: 18)

QUESTION: 69

Explanation:

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QUESTION: 70

Explanation:

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QUESTION: 71

Explanation:

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QUESTION: 72

Explanation:

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