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Salesforce Data-Con-101 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Data Cloud Setup and Administration: This domain focuses on configuring and managing Data Cloud environments through permissions, data streams, data bundles, and data spaces. It also covers administrative tools and techniques for diagnosing and exploring data using reports, dashboards, flows, APIs, and explorer tools.
Thema 2	Segmentation and Insights: This domain centers on creating audience segments and deriving analytical insights from Data Cloud. It includes configuring and maintaining segments, analyzing membership scenarios, and distinguishing between calculated insights and real-time streaming insights.
Thema 3	Act on Data: This domain focuses on leveraging Data Cloud data for downstream actions through activations and data actions. It covers working with attributes, managing timing dependencies, troubleshooting activation issues like errors and rejected counts, and understanding requirements for triggering automated processes.
Thema 4	Data Ingestion and Modeling: This domain addresses bringing data into Data Cloud and structuring it properly through transformation, ingestion from various sources, and data mapping. It emphasizes best practices for modeling data to support identity resolution and validating ingested data using available tools.
Thema 5	Data Cloud Overview: This domain covers the foundational understanding of Data Cloud including its core purpose, terminology, business value, and technical architecture. It also addresses typical use cases and the essential principles of ethical data handling when working with customer data.

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Data-Con-101 Prüfungsaufgaben, Data-Con-101 Testengine

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Salesforce Certified Data Cloud Consultant Data-Con-101 Prüfungsfragen mit Lösungen (Q44-Q49):

44. Frage
Cloud Kicks received a Request to be Forgotten by a customer.
In which two ways should a consultant use Data Cloud to honor this request?
Choose 2 answers

A. Use the Consent API to suppress processing and delete the Individual and related records fromsource data streams.
B. Add the Individual ID to a headerless file and use the delete from file functionality.
C. Delete the data from the incoming data stream and perform a full refresh.
D. Use Data Explorer to locate and manually remove the Individual.

Antwort: A,B

Begründung:
To honor a Request to be Forgotten by a customer, a consultant should use Data Cloud in two ways:
Add the Individual ID to a headerless file and use the delete from file functionality. This option allows the consultant to delete multiple Individuals from Data Cloud by uploading a CSV file with their IDs1. The deletion process is asynchronous and can take up to 24 hours to complete1.
Use the Consent API to suppress processing and delete the Individual and related records from source data streams. This option allows the consultant to submit a Data Deletion request for an Individual profile in Data Cloud using the Consent API2. A Data Deletion request deletes the specified Individual entity and any entities where a relationship has been defined between that entity's identifying attribute and the Individual ID attribute2. The deletion process is reprocessed at 30, 60, and 90 days to ensure a full deletion2. The other options are not correct because:
Deleting the data from the incoming data stream and performing a full refresh will not delete the existing data in Data Cloud, only the new data from the source system3.
Using Data Explorer to locate and manually remove the Individual will not delete the related records from the source data streams, only the Individual entity in Data Cloud. References:
Delete Individuals from Data Cloud
Requesting Data Deletion or Right to Be Forgotten
Data Refresh for Data Cloud
[Data Explorer]

45. Frage
A consultant has an activation that is set to publish every 12 hours, but has discovered that updates to the data prior to activation are delayed by up to 24 hours.
Which two areas should a consultant review to troubleshoot this issue?
Choose 2 answers

A. Review data transformations to ensure they're run after calculated insights.
B. Review calculated insights to make sure they're run before segments are refreshed.
C. Review calculated insights to make sure they're run after the segments are refreshed.
D. Review segments to ensure they're refreshed after the data is ingested.

Antwort: B,D

Begründung:
The correct answer is B and C because calculated insights and segments are both dependent on the data ingestion process. Calculated insights are derived from the data model objects and segments are subsets of data model objects that meet certain criteria. Therefore, both of them need to be updated after the data is ingested to reflect the latest changes. Data transformations are optional steps that can be applied to the data streams before they are mapped to the data model objects, so they are not relevant to the issue. Reviewing calculated insights to make sure they're run after the segments are refreshed (option D) is also incorrect because calculated insights are independent of segments and do not need to be refreshed after them. References: Salesforce Data Cloud Consultant Exam Guide, Data Ingestion and Modeling, Calculated Insights, Segments

46. Frage
A segment fails to refresh with the error "Segment references too many data lake objects (DLOS)".
Which two troubleshooting tips should help remedy this issue?
Choose 2 answers

A. Refine segmentation criteria to limit up to five custom data model objects (DMOs).
B. Use calculated insights in order to reduce the complexity of the segmentation query.
C. Split the segment into smaller segments.
D. Space out the segment schedules to reduce DLO load.

Antwort: B,C

Begründung:
The error "Segment references too many data lake objects (DLOs)" occurs when a segment query exceeds the limit of 50 DLOs that can be referenced in a single query. This can happen when the segment has too many filters, nested segments, or exclusion criteria that involve different DLOs. To remedy this issue, the consultant can try the following troubleshooting tips:
Split the segment into smaller segments. The consultant can divide the segment into multiple segments that have fewer filters, nested segments, or exclusion criteria. This can reduce the number of DLOs that are referenced in each segment query and avoid the error. The consultant can then use the smaller segments as nested segments in a larger segment, or activate them separately.
Use calculated insights in order to reduce the complexity of the segmentation query. The consultant can create calculated insights that are derived from existing data using formulas. Calculated insights can simplify the segmentation query by replacing multiple filters or nested segments with a single attribute. For example, instead of using multiple filters to segment individuals based on their purchase history, the consultant can create a calculated insight that calculates the lifetime value of each individual and use that as a filter.
The other options are not troubleshooting tips that can help remedy this issue. Refining segmentation criteria to limit up to five custom data model objects (DMOs) is not a valid option, as the limit of 50 DLOs applies to both standard and custom DMOs. Spacing out the segment schedules to reduce DLO load is not a valid option, as the error is not related to the DLO load, but to the segment query complexity.
Troubleshoot Segment Errors
Create a Calculated Insight
Create a Segment in Data Cloud

47. Frage
A customer has outlined requirements to trigger a journey for an abandoned browse behavior. Based on the requirements, the consultant determines they will use streaming insights to trigger a data action to Journey Builder every hour.
How should the consultant configure the solution to ensure the data action is triggered at the cadence required?

A. Set the insights aggregation time window to 1 hour.
B. Set the activation schedule to hourly.
C. Set the journey entry schedule to run every hour.
D. Configure the data to be ingested in hourly batches.

Antwort: C

Begründung:
Explanation:

48. Frage
A consultant is discussing the benefits of Data Cloud with a customer that has multiple disjointed data sources.
Which two functional areas should the consultant highlight in relation to managing customer data?
Choose 2 answers

A. Data Marketplace
B. Master Data Management
C. Data Harmonization
D. Unified Profiles

Antwort: C,D

Begründung:
Data Cloud is an open and extensible data platform that enables smarter, more efficient AI with secure access to first-party and industry data1. Two functional areas that the consultant should highlight in relation to managing customer data are:
Data Harmonization: Data Cloud harmonizes data from multiple sources and formats into a common schema, enabling a single source of truth for customer data1. Data Cloud also applies data quality rules and transformations to ensure data accuracy and consistency.
Unified Profiles: Data Cloud creates unified profiles of customers and prospects by linking data across different identifiers, such as email, phone, cookie, and device ID1. Unified profiles provide a holistic view of customer behavior, preferences, and interactions across channels and touchpoints. The other options are not correct because:
Master Data Management: Master Data Management (MDM) is a process of creating and maintaining a single, consistent, and trusted source of master data, such as product, customer, supplier, or location data.
Data Cloud does not provide MDM functionality, but it can integrate with MDM solutions to enrich customer data.
Data Marketplace: Data Marketplace is a feature of Data Cloud that allows users to discover, access, and activate data from third-party providers, such as demographic, behavioral, and intent data. Data Marketplace is not a functional area related to managing customer data, but rather a source of external data that can enhance customer data. References:
Salesforce Data Cloud
[Data Harmonization for Data Cloud]
[Unified Profiles for Data Cloud]
[What is Master Data Management?]
[Integrate Data Cloud with Master Data Management]
[Data Marketplace for Data Cloud]

49. Frage
......

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