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Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • Data Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
Topic 2
  • Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.
Topic 3
  • Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.

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Salesforce Certified Data 360 Consultant (Data-Con-101) Sample Questions (Q104-Q109):

NEW QUESTION # 104
A Data Cloud consultant recently discovered that their identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual.
What should the consultant do to address this issue?

Answer: D

Explanation:
Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency. Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution. References: Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.


NEW QUESTION # 105
A consultant wants to make sure address details from customer orders are selected as best to save to the unified profile.
What should the consultant do to achieve this?

Answer: B

Explanation:
* Unified Profile: Creating a unified customer profile in Salesforce Data Cloud involves consolidating data from various sources.
* Reconciliation Rules: These rules determine which data source is considered the "best" when conflicting data is encountered. Changing reconciliation rules allows prioritizing specific sources.
* Source Priority: Setting source priority involves defining which data source should be preferred over others for specific attributes.
* Process:
Step 1: Access the Data Cloud settings for reconciliation rules.
Step 2: Select the Contact Point Address details.
Step 3: Change the reconciliation rules for address attributes to "Source Priority." Step 4: Move the Order DMO to the top of the priority list. This ensures that address details from customer orders are prioritized and selected as the best data to save to the unified profile.
* Benefits:
Accuracy: Ensures the most accurate and reliable address data is used in the unified profile.
Relevance: Gives priority to the most relevant and frequently updated source (customer orders).
* Reference:
Salesforce Data Cloud Reconciliation Rules
Salesforce Unified Customer Profile


NEW QUESTION # 106
A Data Cloud consultant recently discovered that their identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual.
What should the consultant do to address this issue?

Answer: D

Explanation:
Identity resolution is the process of linking source profiles from different data sources into unified individual profiles based on match and reconciliation rules. If the identity resolution process is matching individuals that share email addresses or phone numbers, but are not actually the same individual, it means that the match rules are too loose and need to be refined. The best way to address this issue is to create and run a new ruleset with stricter matching criteria, such as adding more attributes or increasing the match score threshold. Then, the consultant can compare the two rulesets to review and verify the results, and see if the new ruleset reduces the false positives and improves the accuracy of the identity resolution. Once the new ruleset is approved, the consultant can migrate to the new ruleset and delete the old one. The other options are incorrect because modifying the existing ruleset can affect the existing unified profiles and cause data loss or inconsistency. Creating and running a new ruleset with fewer matching rules can increase the false negatives and reduce the coverage of the identity resolution. Reference: Create Unified Individual Profiles, AI-based Identity Resolution: Linking Diverse Customer Data, Data Cloud Identiy Resolution.


NEW QUESTION # 107
A consultant is ingesting a list of employees from their human resources database that they want to segment on.
Which data stream category should the consultant choose when ingesting this data?

Answer: A

Explanation:
* Categories of Data Streams:
Profile Data: Customer profiles and demographic information.
Contact Data: Contact points like email and phone numbers.
Other Data: Miscellaneous data that doesn't fit into the other categories.
Engagement Data: Interactions and behavioral data.
Reference:
* Ingesting Employee Data:
Employee data typically doesn't fit into profile, contact, or engagement categories meant for customer data.
"Other Data" is appropriate for non-customer-specific data like employee information.
* Steps to Ingest Employee Data:
Navigate to the data ingestion settings in Salesforce Data Cloud.
Select "Create New Data Stream" and choose the "Other Data" category.
Map the fields from the HR database to the corresponding fields in Data Cloud.
* Practical Application:
Example: A company ingests employee data to segment internal communications or analyze workforce metrics.
Choosing the "Other Data" category ensures that this non-customer data is correctly managed and utilized.


NEW QUESTION # 108
A consultant is setting up a data stream with transactional data,
Which field type should the consultant choose to ensure that leading
zeros in the purchase order number are preserved?

Answer: B

Explanation:
The field type Text should be chosen to ensure that leading zeros in the purchase order number are preserved. This is because text fields store alphanumeric characters as strings, and do not remove any leading or trailing characters. On the other hand, number, decimal, and serial fields store numeric values as numbers, and automatically remove any leading zeros when displaying or exporting the data123. Therefore, text fields are more suitable for storing data that needs to retain its original format, such as purchase order numbers, zip codes, phone numbers, etc. References:
Zeros at the start of a field appear to be omitted in Data Exports
Keep First '0' When Importing a CSV File
Import and export address fields that begin with a zero or contain a plus symbol


NEW QUESTION # 109
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