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| Section | Weight | Objectives |
|---|---|---|
| Act on Data | 18% | - Troubleshoot common problems with activations - Use data actions and identify their requirements and intended use cases - Identify and analyze timing dependencies affecting the Data Cloud lifecycle - Define activations and their basic use cases - Use attributes and related attributes |
| Identity Resolution | 14% | - Reconcile data and rule sets - Matching and rule sets |
| Data Cloud Setup and Administration | 12% | - Diagnose and explore data using Data Explorer, Profile Explorer, and APIs - Identify use cases for data spaces and create data spaces based on requirements - Apply Data Cloud permissions, permission sets, and org-wide settings - Describe and configure the available data stream types and data bundles - Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits |
| Solution Overview | 18% | - Describe and apply the principles of data ethics - Articulate how Data Cloud works and its dependencies - Describe Data Cloud's function, key terminology, and business value - Identify typical use cases for Data Cloud |
| Data Ingestion and Modeling | 20% | - Inspect and validate ingested and modeled data - Define, map, and model data for identity resolution - Data ingestion from different sources into Data Cloud - Transformation capabilities (streaming and batch) |
| Segmentation and Insights | 18% | - Identify scenarios for analyzing segment membership - Define basic concepts of segmentation and use cases - Configure, refine, and maintain segments within Data Cloud - Identify and differentiate between calculated and streaming insights |
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NEW QUESTION # 51
A user is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
Answer: C
Explanation:
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. References: Use Value Suggestions in Segmentation, Data Cloud Limits and Guidelines
NEW QUESTION # 52
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?
Answer: D
Explanation:
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.
NEW QUESTION # 53
A Data Cloud consultant recently added a new data source and mapped some of the data to a new custom data model object (DMO) that they want to use for creating segments. However, they cannot view the newly created DMO when trying to create a new segment.
What is the cause of this issue?
Answer: A
Explanation:
The cause of this issue is that the new custom data model object (DMO) is not of category Profile. A category is a property of a DMO that defines its purpose and functionality in Data Cloud. There are three categories of DMOs: Profile, Event, and Other. Profile DMOs are used to store attributes of individuals or entities, such as name, email, address, etc. Event DMOs are used to store actions or interactions of individuals or entities, such as purchases, clicks, visits, etc. Other DMOs are used to store any other type of data that does not fit into the Profile or Event categories, such as products, locations, categories, etc. Only Profile DMOs can be used for creating segments in Data Cloud, as segments are based on the attributes of individuals or entities. Therefore, if the new custom DMO is not of category Profile, it will not appear in the segmentation canvas. The other options are not correct because they are not the cause of this issue. Data ingestion is not a prerequisite for creating segments, as segments can be created based on the data model schema without actual data. The new DMO does not need to have a relationship to the individual DMO, as segments can be created based on any Profile DMO, regardless of its relationship to other DMOs. Segmentation is not only supported for the Individual and Unified Individual DMOs, as segments can be created based on any Profile DMO, including custom ones. References: Create a Custom Data Model Object from an Existing Data Model Object, Create a Segment in Data Cloud, Data Model Object Category
NEW QUESTION # 54
Northern Trail Outfitters uses B2C Commerce and is exploring implementing Data Cloud to get a unified view of its customers and all their order transactions.
What should the consultant keep in mind with regard to historical data ingesting order data using the B2C Commerce Order Bundle?
Answer: C
Explanation:
The B2C Commerce Order Bundle is a data bundle that creates a data stream to flow order data from a B2C Commerce instance to Data Cloud. However, this data bundle does not ingest any historical data and only ingests new orders from the time the data stream is created. Therefore, if a consultant wants to ingest historical order data, they need to use a different method, such as exporting the data from B2C Commerce and importing it to Data Cloud using a CSV file12. References:
Create a B2C Commerce Data Bundle
Data Access and Export for B2C Commerce and Commerce Marketplace
NEW QUESTION # 55
A Data Cloud consultant tries to save a new 1-to-l relationship between the Account DMO and Contact Point Address DMO but gets an error.
What should the consultant do to fix this error?
Answer: C
NEW QUESTION # 56
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