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| Section | Weight | Objectives |
|---|---|---|
| Segmentation and Insights | 18% | - Configure, refine, and maintain segments within Data Cloud - Define basic concepts of segmentation and use cases - Identify scenarios for analyzing segment membership - Identify and differentiate between calculated and streaming insights |
| Solution Overview | 18% | - Identify typical use cases for Data Cloud - Describe Data Cloud's function, key terminology, and business value - Articulate how Data Cloud works and its dependencies - Describe and apply the principles of data ethics |
| Act on Data | 18% | - Define activations and their basic use cases - Use data actions and identify their requirements and intended use cases - Identify and analyze timing dependencies affecting the Data Cloud lifecycle - Use attributes and related attributes - Troubleshoot common problems with activations |
| Identity Resolution | 14% | - Reconcile data and rule sets - Matching and rule sets |
| Data Cloud Setup and Administration | 12% | - Describe and configure the available data stream types and data bundles - Apply Data Cloud permissions, permission sets, and org-wide settings - Identify use cases for data spaces and create data spaces based on requirements - Diagnose and explore data using Data Explorer, Profile Explorer, and APIs - Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits |
| Data Ingestion and Modeling | 20% | - Data ingestion from different sources into Data Cloud - Define, map, and model data for identity resolution - Inspect and validate ingested and modeled data - Transformation capabilities (streaming and batch) |
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NEW QUESTION # 86
What should an organization use to stream inventory levels from an inventory management system into Data Cloud in a fast and scalable, near-real-time way?
Answer: B
Explanation:
The Ingestion API is a RESTful API that allows you to stream data from any source into Data Cloud in a fast and scalable way. You can use the Ingestion API to send data from your inventory management system into Data Cloud as JSON objects, and then use Data Cloud to create data models, segments, and insights based on your inventory data. The Ingestion API supports both batch and streaming modes, and can handle up to
100,000 records per second. The Ingestion API also provides features such as data validation, encryption, compression, and retry mechanisms to ensure data quality and security. References: Ingestion API Developer Guide, Ingest Data into Data Cloud
NEW QUESTION # 87
When performing segmentation or activation, which time zone is used to publish and refresh data?
Answer: D
Explanation:
The time zone that is used to publish and refresh data when performing segmentation or activation is D. Time zone set by the Salesforce Data Cloud org. This time zone is the one that is configured in the org settings when Data Cloud is provisioned, and it applies to all users and activities in Data Cloud. This time zone determines when the segments are scheduled to refresh and when the activations are scheduled to publish.
Therefore, it is important to consider the time zone difference between the Data Cloud org and the destination systems or channels when planning the segmentation and activation strategies. References: Salesforce Data Cloud Consultant Exam Guide, Segmentation, Activation
NEW QUESTION # 88
Cumulus Financial is currently using Data Cloud and ingesting transactional data from its backend system via an S3 Connector in upsert mode. During the initial setup six months ago, the company created a formula field in Data Cloud to create a custom classification. It now needs to update this formula to account for more classifications.
What should the consultant keep in mind with regard to formula field updates when using the S3 Connector?
Answer: D
NEW QUESTION # 89
A user Is not seeing suggested values from newly-modeled data when building a segment.
What is causing this issue?
Answer: C
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 # 90
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?
Answer: A
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 # 91
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