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Data-Cloud-Consultant Mit Hilfe von uns können Sie bedeutendes Zertifikat der Data-Cloud-Consultant einfach erhalten!
Die Salesforce Data-Cloud-Consultant (Salesforce Certified Data Cloud Consultant) Zertifizierungsprüfung ist eine Prüfung, die Fachkenntnisse und Fertigkeiten eines Menschen testet. Wenn Sie einen Job in der IT-Branche suchen, werden Sie viele Personalmanager nach den relevanten Salesforce Data-Cloud-Consultant IT-Zertifikaten fragen. Wenn Sie das Salesforce Data-Cloud-Consultant (Salesforce Certified Data Cloud Consultant) Zertifikat haben, können Sie sicher Ihre Wettbewerbsfähigkeit verstärken.
Salesforce Data-Cloud-Consultant Prüfungsplan:
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Data-Cloud-Consultant Übungsfragen: Salesforce Certified Data Cloud Consultant & Data-Cloud-Consultant Dateien Prüfungsunterlagen
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Salesforce Certified Data Cloud Consultant Data-Cloud-Consultant Prüfungsfragen mit Lösungen (Q167-Q172):
167. Frage
A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud.
Where does a request for data deletion or right to be forgotten get submitted?
- A. In Data Cloud settings
- B. On the individual data profile in Data Cloud
- C. through Consent API
- D. In Marketing Cloud settings
Antwort: D
Begründung:
Data Deletion Requests: For companies using Salesforce Marketing Cloud and Data Cloud, managing data privacy and deletion requests is essential.
Marketing Cloud Connector: This connector facilitates data integration between Marketing Cloud and Data Cloud, but data deletion requests must follow specific procedures.
Deletion Requests in Marketing Cloud:
* Data Management: Requests for data deletion or the right to be forgotten are submitted through Marketing Cloud settings, where the customer data is originally stored and managed.
* Propagation: Once the request is processed in Marketing Cloud, the changes are propagated to Data Cloud through the connector.
References:
* Salesforce Marketing Cloud Documentation: Data Management
* Salesforce Data Cloud Connector Guide
168. Frage
A consultant at Northern Trail Outfitters is attempting to ingest a field from the Contact object in Salesforce CRM that contains both yyyy-mm-dd and yyyy-mm-dd hh:mm:ss values. The target field is set to Date datatype.
Which statement is true in this situation?
- A. The target field will throw an error and store null values.
- B. The target field will only hold the time part and ignore the date part.
- C. The target field will be able to hold both types of values.
- D. The target field will only hold the date part and ignore the time part.
Antwort: D
Begründung:
Field Data Types: Salesforce CRM's Contact object fields can store data in various formats. When ingesting data into Salesforce Data Cloud, the target field's data type determines how the data is processed and stored.
Date Data Type: If the target field in Data Cloud is set to Date data type, it is designed to store date values without time information.
Mixed Format Values: When ingesting a field containing both date (yyyy-mm-dd) and datetime (yyyy-mm-dd hh:mm:ss) values into a Date data type field:
* The Date field will extract and store only the date part (yyyy-mm-dd), ignoring the time part (hh:mm:ss).
Result:
* Date Values: yyyy-mm-dd values are stored as-is.
* Datetime Values: yyyy-mm-dd hh:mm:ss values are truncated to yyyy-mm-dd, and the time component is ignored.
References:
* Salesforce Data Cloud Field Mapping
* Salesforce Data Types
169. Frage
Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud.
In what order should each process be run to ensure that freshly imported data is ready and available to use for any segment?
- A. Identity Resolution > Refresh Data Stream > Calculated Insight
- B. Refresh Data Stream > Calculated Insight > Identity Resolution
- C. Refresh Data Stream > Identity Resolution > Calculated Insight
- D. Calculated Insight > Refresh Data Stream > Identity Resolution
Antwort: C
Begründung:
To ensure that freshly imported data from an Amazon S3 Bucket is ready and available to use for any segment, the following processes should be run in this order:
* Refresh Data Stream: This process updates the data lake objects in Data Cloud with the latest data from the source system. It can be configured to run automatically or manually, depending on the data stream
* settings1. Refreshing the data stream ensures that Data Cloud has the most recent and accurate data from the Amazon S3 Bucket.
* Identity Resolution: This process creates unified individual profiles by matching and consolidating source profiles from different data streams based on the identity resolution ruleset. It runs daily by default, but can be triggered manually as well2. Identity resolution ensures that Data Cloud has a single view of each customer across different data sources.
* Calculated Insight: This process performs calculations on data lake objects or CRM data and returns a result as a new data object. It can be used to create metrics or measures for segmentation or analysis purposes3. Calculated insights ensure that Data Cloud has the derived data that can be used for personalization or activation.
References:
* 1: Configure Data Stream Refresh and Frequency - Salesforce
* 2: Identity Resolution Ruleset Processing Results - Salesforce
* 3: Calculated Insights - Salesforce
170. Frage
Which configuration supports separate Amazon S3 buckets for data ingestion and activation?
- A. Separate user credentials for data stream and activation target
- B. Dedicated S3 data sources in activation setup
- C. Dedicated S3 data sources in Data Cloud setup
- D. Multiple S3 connectors in Data Cloud setup
Antwort: C
Begründung:
To support separate Amazon S3 buckets for data ingestion and activation, you need to configure dedicated S3 data sources in Data Cloud setup. Data sources are used to identify the origin and type of the data that you ingest into Data Cloud1. You can create different data sources for each S3 bucket that you want to use for ingestion or activation, and specify the bucket name, region, and access credentials2. This way, you can separate and organize your data by different criteria, such as brand, region, product, or business unit3. The other options are incorrect because they do not support separate S3 buckets for data ingestion and activation. Multiple S3 connectors are not a valid configuration in Data Cloud setup, as there is only one S3 connector available4. Dedicated S3 data sources in activation setup are not a valid configuration either, as activation setup does not require data sources, but activation targets5. Separate user credentials for data stream and activation target are not sufficient to support separate S3 buckets, as you also need to specify the bucket name and region for each data source2. References: Data Sources Overview, Amazon S3 Storage Connector, Data Spaces Overview, Data Streams Overview, Data Activation Overview
171. Frage
Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud. Based on this, a calculated insight is created that shows the total spend per customer in the last
30 days.
In which sequence should each process be run to ensure that freshly imported data is ready and available to use for any segment?
- A. Identity Resolution > Refresh Data Stream > Calculated Insight
- B. Refresh Data Stream > Calculated Insight > Identity Resolution
- C. Refresh Data Stream > Identity Resolution > Calculated Insight
- D. Calculated Insight > Refresh Data Stream > Identity Resolution
Antwort: C
Begründung:
To ensure that freshly imported data is ready and available for use in any segment, the processes should be run in the following sequence: Refresh Data Stream > Identity Resolution > Calculated Insight . Here's why:
Understanding the Requirement
Northern Trail Outfitters uploads new customer data daily to an Amazon S3 bucket, which is ingested into Data Cloud.
A calculated insight is created to show the total spend per customer in the last 30 days.
The goal is to ensure that the data is properly refreshed, resolved, and processed before being used in segments.
Why This Sequence?
Step 1: Refresh Data Stream
Before any processing can occur, the data stream must be refreshed to ingest the latest data from the Amazon S3 bucket.
This ensures that the most up-to-date customer data is available in Data Cloud.
Step 2: Identity Resolution
After refreshing the data stream, identity resolution must be performed to merge related records into unified profiles.
This step ensures that customer data is consolidated and ready for analysis.
Step 3: Calculated Insight
Once identity resolution is complete, the calculated insight can be generated to calculate the total spend per customer in the last 30 days.
This ensures that the insight is based on the latest and most accurate data.
Other Options Are Incorrect :
B). Refresh Data Stream > Calculated Insight > Identity Resolution : Calculated insights cannot be generated before identity resolution because they rely on unified profiles.
C). Calculated Insight > Refresh Data Stream > Identity Resolution : Calculated insights require both fresh data and resolved identities, so this sequence is invalid.
D). Identity Resolution > Refresh Data Stream > Calculated Insight : Identity resolution cannot occur without first refreshing the data stream to bring in the latest data.
Conclusion
The correct sequence is Refresh Data Stream > Identity Resolution > Calculated Insight , ensuring that the data is properly refreshed, resolved, and processed before being used in segments.
172. Frage
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