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Salesforce Data-Con-101 Exam Syllabus Topics:

Topic
Details

Topic 1

Data Cloud Overview: This domain covers the foundational understanding of Data Cloud including its core purpose, terminology, business value, and technical architecture. It also addresses typical use cases and the essential principles of ethical data handling when working with customer data.

Topic 2

Segmentation and Insights: This domain centers on creating audience segments and deriving analytical insights from Data Cloud. It includes configuring and maintaining segments, analyzing membership scenarios, and distinguishing between calculated insights and real-time streaming insights.

Topic 3

Data Ingestion and Modeling: This domain addresses bringing data into Data Cloud and structuring it properly through transformation, ingestion from various sources, and data mapping. It emphasizes best practices for modeling data to support identity resolution and validating ingested data using available tools.

Topic 4

Data Cloud Setup and Administration: This domain focuses on configuring and managing Data Cloud environments through permissions, data streams, data bundles, and data spaces. It also covers administrative tools and techniques for diagnosing and exploring data using reports, dashboards, flows, APIs, and explorer tools.

Topic 5

Identity Resolution: This domain explores creating unified customer profiles through matching and reconciliation processes. It covers how rule sets determine when records link together, how conflicting data is resolved, and understanding the outcomes and use cases of unified identities.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q157-Q162):

NEW QUESTION # 157
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 be able to hold both types of values.
B. The target field will only hold the time part and ignore the date part.
C. The target field will only hold the date part and ignore the time part.
D. The target field will throw an error and store null values.

Answer: C

Explanation:
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

NEW QUESTION # 158
What does the Ignore Empty Value option do in identity resolution?

A. Ignores Individual object records with empty fields when running identity resolution rules
B. Ignores empty fields when running reconciliation rules
C. Ignores empty fields when running any custom match rules
D. Ignores empty fields when running the standard match rules

Answer: B

Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
Data Cloud Identity Resolution Reconciliation Rule Input
Configure Identity Resolution Rulesets
Data and Identity in Data Cloud

NEW QUESTION # 159
Which statement is true related to batch ingestions from Salesforce CRM?

A. CRM data cannot be manually refreshed and must wait for the next scheduled synchronization.
B. When a column is added or removed, the CRM connector performs a full refresh.
C. The CRM connector performs an incremental refresh when 600K or more deletion records are detected.
D. The CRM connector's synchronization times can be customized to up to 15-minute intervals.

Answer: B

Explanation:
The question asks which statement is true about batch ingestions from Salesforce CRM into Salesforce Data Cloud. Batch ingestion refers to the process of periodically syncing data from Salesforce CRM (e.g., Accounts, Contacts, Opportunities) into Data Cloud. The focus is on how the CRM connector handles changes in data structure (e.g., adding or removing columns) and synchronization behavior.
Why A is Correct: "When a column is added or removed, the CRM connector performs a full refresh." Behavior of the CRM Connector :
The Salesforce CRM connector automatically detects schema changes, such as when a field (column) is added or removed in the source CRM object.
When such changes occur, the CRM connector triggers a full refresh of the data for that object. This ensures that the data model in Data Cloud aligns with the updated schema in Salesforce CRM.
Why a Full Refresh is Necessary :
A full refresh ensures that all records are re-ingested with the updated schema, avoiding inconsistencies or missing data caused by incremental updates.
Incremental updates only capture changes (e.g., new or modified records), so they cannot handle schema changes effectively.
Other Options Are Incorrect :
B). The CRM connector performs an incremental refresh when 600K or more deletion records are detected :
This is incorrect because the CRM connector does not switch to incremental refresh based on the number of deletion records. It always performs incremental updates unless a schema change triggers a full refresh.
C). The CRM connector's synchronization times can be customized to up to 15-minute intervals : While synchronization schedules can be customized, the minimum interval is typically 1 hour , not 15 minutes.
D). CRM data cannot be manually refreshed and must wait for the next scheduled synchronization : This is incorrect because users can manually trigger a refresh of CRM data in Data Cloud if needed.
Steps to Understand CRM Connector Behavior
Step 1: Schema Changes Trigger Full Refresh
If a field is added or removed in Salesforce CRM, the CRM connector detects this change and initiates a full refresh of the corresponding object in Data Cloud.
Step 2: Incremental Updates for Regular Syncs
For regular synchronization, the CRM connector performs incremental updates, capturing only new or modified records since the last sync.
Step 3: Manual Refresh Option
Users can manually trigger a refresh in Data Cloud if immediate synchronization is required, bypassing the scheduled sync.
Step 4: Monitor Synchronization Logs
Use the Data Cloud Monitoring tools to track synchronization status, including full refreshes and incremental updates.
Conclusion
The statement "When a column is added or removed, the CRM connector performs a full refresh" is true. This behavior ensures that the data model in Data Cloud remains consistent with the schema in Salesforce CRM, avoiding potential data integrity issues.

NEW QUESTION # 160
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?

A. Value suggestion requires Data Aware Specialist permissions at a minimum.
B. Value suggestion will only return results for the first 50 values of a specific attribute,
C. Value suggestion can only work on direct attributes and not related attributes.
D. Value suggestion is still processing and takes up to 24 hours to be available.

Answer: D

Explanation:
The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature. References:
Use Value Suggestions in Segmentation

NEW QUESTION # 161
How does identity resolution select attributes for unified individuals when there Is conflicting information in the data model?

A. Creates additional rulesets
B. Creates additional contact points
C. Leverages match rules
D. Leverages reconciliation rules

Answer: D

Explanation:
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. References: Identity Resolution, Reconciliation Rules, Salesforce Data Cloud Exam Questions

NEW QUESTION # 162
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