今後のData-Con-101学習教材について心配がある場合は、学習教材が問題の解決に役立ちます。弊社のData-Con-101学習教材の高品質をお約束するために、当社には優れた技術スタッフがおり、販売後の完璧なサービスシステムがあります。さらに重要なことは、当社のData-Con-101ガイド質問と完璧なアフターサービスが、地元および海外のお客様に認められていることです。模擬試験に合格する場合は、学習エンジンが必須の選択肢になると考えています。過去数年間、Data-Con-101ガイドの質問を購入する人が増えています。
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identity Resolution | 14% | - Reconcile data and rule sets - Matching and rule sets |
| Topic 2: Act on Data | 18% | - Use attributes and related attributes - Identify and analyze timing dependencies affecting the Data Cloud lifecycle - Use data actions and identify their requirements and intended use cases - Troubleshoot common problems with activations - Define activations and their basic use cases |
| Topic 3: Solution Overview | 18% | - Identify typical use cases for Data Cloud - Articulate how Data Cloud works and its dependencies - Describe Data Cloud's function, key terminology, and business value - Describe and apply the principles of data ethics |
| Topic 4: Data Ingestion and Modeling | 20% | - Data ingestion from different sources into Data Cloud - Inspect and validate ingested and modeled data - Define, map, and model data for identity resolution - Transformation capabilities (streaming and batch) |
| Topic 5: Segmentation and Insights | 18% | - Identify scenarios for analyzing segment membership - Configure, refine, and maintain segments within Data Cloud - Define basic concepts of segmentation and use cases - Identify and differentiate between calculated and streaming insights |
| Topic 6: Data Cloud Setup and Administration | 12% | - Describe and configure the available data stream types and data bundles - Diagnose and explore data using Data Explorer, Profile Explorer, and APIs - Apply Data Cloud permissions, permission sets, and org-wide settings - Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits - Identify use cases for data spaces and create data spaces based on requirements |
望ましい仕事を見つけるのに十分な競争力がないと感じたら、 あなたはData-Con-101認定試験資格証明書を取得するべきです。 私たちのData-Con-101試験教材は、あなたが就職市場で最も一般的なスキルを身につけるのに役立ちます。 そうすれば、望ましい仕事を見つけることができます。 また、私たちのData-Con-101試験教材に関する基礎知識があるかどうかは構わないです。実際Data-Con-101試験に対して試験ガイドがあります。
質問 # 63
How does Data Cloud handle an individual's Right to be Forgotten?
正解：C
解説：
Data Cloud handles an individual's Right to be Forgotten by deleting the specified Individual and records from any data model object/data lake object related to the Individual. This means that Data Cloud removes all the data associated with the individual from the data space, including the data from the source objects, the unified individual profile, and any related objects. Data Cloud also deletes the Unified Individual Link record that links the individual to the source records. Data Cloud uses the Consent API to process the Right to be Forgotten requests, which are reprocessed at 30, 60, and 90 days to ensure a full deletion.
The other options are not correct descriptions of how Data Cloud handles an individual's Right to be Forgotten. Data Cloud does not delete the records from all data source objects, as this would affect the data integrity and availability of the source systems. Data Cloud also does not delete only the specified Individual record and its Unified Individual Link record, as this would leave the source records and the related records intact. Data Cloud also does not delete only the specified Individual and records from any data source object mapped to the Individual data model object, as this would leave the related records intact.
Requesting Data Deletion or Right to Be Forgotten
Data Deletion for Data Cloud
Use the Consent API with Data Cloud
Data and Identity in Data Cloud
質問 # 64
Which statement about Data Cloud's Web and Mobile Application Connector is true?
正解：A
解説：
The Web and Mobile Application Connector allows you to ingest data from your websites and mobile apps into Data Cloud. To use this connector, you need to set up a Tenant Specific Endpoint (TSE) in Data Cloud, which is a unique URL that identifies your Data Cloud org. The TSE is auto-generated when you create a connector app in Data Cloud Setup. You can then use the TSE to configure the SDKs for your websites and mobile apps, which will send data to Data Cloud through the TSE. References: Web and Mobile Application Connector, Connect Your Websites and Mobile Apps, Create a Web or Mobile App Data Stream
質問 # 65
Where is value suggestion for attributes in segmentation enabled when creating the DMO?
正解：B
解説：
Value suggestion for attributes in segmentation is a feature that allows you to see and select the possible values for a text field when creating segment filters. You can enable or disable this feature for each data model object (DMO) field in the DMO record home. Value suggestion can be enabled for up to 500 attributes for your entire org. It can take up to 24 hours for suggested values to appear. To use value suggestion when creating segment filters, you need to drag the attribute onto the canvas and start typing in the Value field for an attribute. You can also select multiple values for some operators. Value suggestion is not available for attributes with more than 255 characters or for relationships that are one-to-many (1:N). References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes
質問 # 66
Cumulus Financial needs to create a composite key on an incoming data source that combines the fields Customer Region and Customer Identifier.
Which formula function should a consultant use to create a composite key when a primary key is not available in a data stream?
正解：A
解説：
Composite Keys in Data Streams: When working with data streams in Salesforce Data Cloud, there may be situations where a primary key is not available. In such cases, creating a composite key from multiple fields ensures unique identification of records.
Formula Functions: Salesforce provides several formula functions to manipulate and combine data fields.
Among them, the CONCAT function is used to combine multiple strings into one.
Creating Composite Keys: To create a composite key using CONCAT, a consultant can combine the values of Customer Region and Customer Identifier into a single unique identifier.
Example Formula: CONCAT(Customer_Region, Customer_Identifier)
References:
Salesforce Documentation: Formula Functions
Salesforce Data Cloud Guide
質問 # 67
The Salesforce CRM Connector is configured and the Case object data stream is set up. Subsequently, a new custom field named Business Priority is created on the Case object in Salesforce CRM. However, the new field is not available when trying to add it to the data stream.
Which statement addresses the cause of this issue?
正解：B
解説：
The Salesforce CRM Connector uses the Salesforce Integration User to access the data from the Salesforce CRM org. The Integration User must have the Read permission on the fields that are included in the data stream. If the Integration User does not have the Read permission on the newly created field, the field will not be available for selection in the data stream configuration. To resolve this issue, the administrator should assign the Read permission on the new field to the Integration User profile or permission set. References: Create a Salesforce CRM Data Stream, Edit a Data Stream, Salesforce Data Cloud Full Refresh for CRM, SFMC, or Ingestion API Data Streams
質問 # 68
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