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| Section | Weight | Objectives |
|---|---|---|
| Data Cloud Monitoring and Troubleshooting | 22% | - Use Data Cloud analytics and reports - Manage data retention and cleanup - Analyze identity resolution results - Debug common configuration errors - Monitor data ingestion and sync status - Troubleshoot data quality issues |
| Data Actions | 8% | - Create and manage data bundles - Configure data actions for activation - Configure data sync to external systems - Set up segmentation and target audiences |
| Data Sharing and Security | 8% | - Understand data governance requirements - Implement row-level security - Manage user access and permissions - Configure data sharing settings |
| Data Model Setup and Configuration | 15% | - Describe Harmonized Data Model concepts - Understand data types and field mapping - Set up and configure Data Lake objects - Configure custom objects, fields, and relationships - Map source data to harmonized data model |
| Identity Resolution and Data Unification | 17% | - Configure identity resolution rules - Understand unified records creation - Configure match rules and strategies - Manage data overlap and deduplication - Configure contact and account matching |
| Data Ingestion | 15% | - Troubleshoot ingestion issues - Configure data sync and refresh schedules - Configure streaming data ingestion - Configure batch data ingestion - Set up and manage data connectors |
| Calculated Insights | 8% | - Define metrics and measurements - Create and configure calculated insights - Use formulas and functions in calculations - Publish insights to Data Cloud |
| Data Cloud Overview and Licensing | 7% | - Describe the business value of Data Cloud - Explain licensing model and capacity - Describe Data Cloud setup and configuration |
>> Data-Cloud-Consultant考古題介紹 <<
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問題 #67
A consultant needs to publish segment data to the Audience DMO that can be retrieved using the Query APIs.
When creating the activation target, which type of target should the consultant select?
答案：C
問題 #68
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
答案：C,D
解題說明：
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. References: Dashboards, Reports
問題 #69
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：A
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. Reference: Calculated Insights, Calculated Insights in a Data Space.
問題 #70
A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of their customers.
Which object should the consultant use in identity resolution to perform exact match rules on the Loyalty ID?
答案：B
解題說明：
The Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals.
The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification object is a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.
References:
* Data Modeling Requirements for Identity Resolution
* Identity Resolution in a Data Space
* Configure Identity Resolution Rulesets
* Map Required Objects
* Data and Identity in Data Cloud
問題 #71
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
答案：A
解題說明：
Value suggestion is a feature that allows users to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature can take up to 24 hours to process and display the values for newly-modeled data. Therefore, if a user is not seeing suggested values from newly-modeled data, it is likely that the value suggestion is still processing and will be available soon. The other options are incorrect because value suggestion does not require any specific permissions, can work on both direct and related attributes, and can return more than 50 values for a specific attribute, depending on the data type and frequency of the values. Reference: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines
問題 #72
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