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| Certification Vendor: | Salesforce |
|---|---|
| Exam Name: | Salesforce Certified Data Cloud Consultant |
| Exam Number: | Data-Con-101 |
| Exam Duration: | 105 minutes |
| Related Certifications: | Salesforce Certified AI Associate |
| Real Exam Qty: | 60 (plus up to 5 unscored questions) |
| Certificate Validity Period: | Maintenance required annually (Trailhead modules) |
| Exam Format: | Multiple-choice, Multiple-select |
| Available Languages: | English |
| Exam Price: | USD 200 |
| Passing Score: | 62% |
| Sample Questions: | Salesforce Data-Con-101 Sample Questions |
| Exam Way: | Online (Webassessor/PSI) or Onsite (Pearson VUE) |
| Pre Condition: | No hard prerequisites; recommended 2+ years of experience in data strategy and data modeling |
| Official Syllabus URL: | https://trailhead.salesforce.com/credentials/datacloudconsultant |
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問題 #22
A customer has a calculated insight about lifetime value.
What does the consultant need to be aware of if the calculated insight.
needs to be modified?
答案：D
解題說明：
A calculated insight is a multidimensional metric that is defined and calculated from data using SQL expressions. A calculated insight can include dimensions and measures. Dimensions are the fields that are used to group or filter the data, such as customer ID, product category, or region. Measures are the fields that are used to perform calculations or aggregations, such as revenue, quantity, or average order value. A calculated insight can be modified by editing the SQL expression or changing the data space. However, the consultant needs to be aware of the following limitations and considerations when modifying a calculated insight12:
Existing dimensions cannot be removed. If a dimension is removed from the SQL expression, the calculated insight will fail to run and display an error message. This is because the dimension is used to create the primary key for the calculated insight object, and removing it will cause a conflict with the existing data.
Therefore, the correct answer is B.
New dimensions can be added. If a dimension is added to the SQL expression, the calculated insight will run and create a new field for the dimension in the calculated insight object. However, the consultant should be careful not to add too many dimensions, as this can affect the performance and usability of the calculated insight.
Existing measures can be removed. If a measure is removed from the SQL expression, the calculated insight will run and delete the field for the measure from the calculated insight object. However, the consultant should be aware that removing a measure can affect the existing segments or activations that use the calculated insight.
New measures can be added. If a measure is added to the SQL expression, the calculated insight will run and create a new field for the measure in the calculated insight object. However, the consultant should be careful not to add too many measures, as this can affect the performance and usability of the calculated insight. References: Calculated Insights, Calculated Insights in a Data Space.
問題 #23
A retail customer wants to bring customer data from different sources
and wants to take advantage of identity resolution so that it can be
used in segmentation.
On which entity should this be segmented for activation membership?
答案：A
解題說明：
The correct answer is B, Unified Individual. A Unified Individual is a record that represents a customer across different data sources, created by applying identity resolution rulesets. Identity resolution rulesets are sets of match and reconciliation rules that define how to link and merge data from different sources based on common attributes. Data Cloud uses identity resolution rulesets to resolve data across multiple data sources and helps you create one record for each customer, regardless of where the data came from1. A retail customer who wants to bring customer data from different sources and use identity resolution for segmentation should segment on the Unified Individual entity, which contains the resolved and consolidated customer data. The other options are incorrect because they do not represent the resolved customer data across different sources. A Subscriber is a record that represents a customer who has opted in to receive marketing communications. A Unified Contact is a record that represents a customer who has a relationship with a specific business unit. An Individual is a record that represents a customer's profile data from a single data source. References:
Identity Resolution Ruleset Processing Results
Consider Data Implications for Segmentation
Prepare for your Salesforce Data Cloud Consultant Credential
AI-based Identity Resolution: Linking Diverse Customer Data
問題 #24
Northern Trail Outfitters (NTO) is configuring an identity resolution ruleset based on Fuzzy Name and Normalized Email.
What should NTO do to ensure the best email address is activated?
答案：C
解題說明：
NTO is using Fuzzy Name and Normalized Email as match rules to link together data from different sources into a unified individual profile. However, there might be cases where the same email address is available from more than one source, and NTO needs to decide which one to use for activation. For example, if Rachel has the same email address in Service Cloud and Marketing Cloud, but prefers to receive communications from NTO via Marketing Cloud, NTO needs to ensure that the email address from Marketing Cloud is activated. To do this, NTO can use the source priority order in activations, which allows them to rank the data sources in order of preference for activation. By placing Marketing Cloud higher than Service Cloud in the source priority order, NTO can make sure that the email address from Marketing Cloud is delivered to the activation target, such as an email campaign or a journey. This way, NTO can respect Rachel's preference and deliver a better customer experience. References: Configure Activations, Use Source Priority Order in Activations
問題 #25
A Data Cloud consultant is evaluating the initial phase of the Data Cloud lifecycle for a company.
Which action is essential to effectively begin the Data Cloud lifecycle?
答案：D
解題說明：
Data Cloud Lifecycle: The initial phase of the Salesforce Data Cloud lifecycle is critical for setting the foundation for successful data integration and utilization.
Identifying Use Cases:
Importance: Defining clear use cases helps in understanding the business objectives and how Data Cloud can address them.
Required Data Sources: Identifying the necessary data sources ensures that relevant data is ingested into Data Cloud.
Data Quality: Assessing data quality is essential for accurate and reliable data analysis and insights.
Actions:
Step 1: Engage with stakeholders to define specific use cases for Data Cloud.
Step 2: Identify and catalog the required data sources for these use cases.
Step 3: Evaluate the quality of data from these sources to ensure they meet the standards for effective data analysis.
References:
Salesforce Data Cloud Implementation Guide
Salesforce Data Cloud Lifecycle
問題 #26
A consultant is helping a beauty company ingest its profile data into Data Cloud. The company's source data includes several fields, such as eye color, skin type, and hair color, that are not fields in the standard Individual data model object (DMO).
What should the consultant recommend to map this data to be used for both segmentation and identity resolution?
答案：D
解題說明：
The best option to map the data to be used for both segmentation and identity resolution is to create custom fields on the standard Individual DMO. This way, the consultant can leverage the existing fields and functionality of the Individual DMO, such as identity resolution rulesets, calculated insights, and data actions, while adding the additional fields that are specific to the beauty company's data1. Creating a custom DMO from scratch or duplicating the standard Individual DMO would require more effort and maintenance, and might not be compatible with the existing features of Data Cloud. Creating a custom DMO with only the additional fields and mapping it to the standard Individual DMO would create unnecessary complexity and redundancy, and might not allow the use of the custom fields for identity resolution. References:
1: Data Model Objects in Data Cloud
問題 #27
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