最高Data-Con-101｜実用的なData-Con-101勉強の資料試験｜試験の準備方法Salesforce Certified Data Cloud Consultant合格体験記

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Salesforce Data-Con-101 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Segmentation and Insights	18%	- Define basic concepts of segmentation and use cases - Configure, refine, and maintain segments within Data Cloud - Identify and differentiate between calculated and streaming insights - Identify scenarios for analyzing segment membership
Topic 2: Solution Overview	18%	- Identify typical use cases for Data Cloud - Describe and apply the principles of data ethics - Describe Data Cloud's function, key terminology, and business value - Articulate how Data Cloud works and its dependencies
Topic 3: Act on Data	18%	- Define activations and their basic use cases - Use data actions and identify their requirements and intended use cases - Use attributes and related attributes - Identify and analyze timing dependencies affecting the Data Cloud lifecycle - Troubleshoot common problems with activations
Topic 4: 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 - 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 - Apply Data Cloud permissions, permission sets, and org-wide settings
Topic 5: 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)
Topic 6: Identity Resolution	14%	- Reconcile data and rule sets - Matching and rule sets

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Data-Con-101合格体験記、Data-Con-101参考書内容

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Salesforce Certified Data Cloud Consultant 認定 Data-Con-101 試験問題 (Q15-Q20):

質問 # 15
A consultant is integrating an Amazon 53 activated campaign with the customer's destination system.
In order for the destination system to find the metadata about the segment, which file on the 53 will contain this information for processing?

A. The .zip file
B. The json file
C. The .txt file
D. The .csv file

正解：B

解説：
The file on the Amazon S3 that will contain the metadata about the segment for processing is B. The json file. The json file is a metadata file that is generated along with the csv file when a segment is activated to Amazon S3. The json file contains information such as the segment name, the segment ID, the segment size, the segment attributes, the segment filters, and the segment schedule. The destination system can use this file to identify the segment and its properties, and to match the segment data with the corresponding fields in the destination system. References: Salesforce Data Cloud Consultant Exam Guide, Amazon S3 Activation

質問 # 16
How does Data Cloud ensure data privacy and security?

A. By securely storing data in an offsite server
B. By enforcing and controlling consent references
C. BY limiting data access to authorized admins
D. By encrypting data at rest and in transit

正解：D

解説：
Data Privacy and Security in Data Cloud:
Ensuring data privacy and security is paramount in Salesforce Data Cloud.
Reference: Salesforce Data Privacy and Security Overview
Key Security Measures:
Encrypting Data at Rest and in Transit:
Data encryption ensures that information is protected from unauthorized access both when stored and when transmitted.
Reference: Salesforce Encryption Documentation
Enforcing and Controlling Consent Preferences:
Consent management ensures that data usage complies with customer permissions and regulatory requirements.
Reference: Salesforce Consent Management Guide
Steps to Implement Security Measures:
Data Encryption:
Enable encryption for data at rest using Salesforce Shield.
Ensure TLS/SSL encryption is used for data in transit.
Consent Management:
Set up and enforce consent preferences within Data Cloud.
Regularly audit and update consent records.
Reference: Salesforce Shield Encryption and Consent Management Implementation Guide Practical Application:
Example: A financial institution uses encryption to secure customer financial data and manages consent to comply with GDPR.
Reference: Salesforce Data Privacy Case Studies

質問 # 17
Cumulus Financial wants to segregate Salesforce CRM Account data based on Country for its Data Cloud users.
What should the consultant do to accomplish this?

A. Use Salesforce sharing rules on the Account object to filter and segregate records based on Country.
B. Use formula fields based on the account Country field to filter incoming records.
C. Use streaming transforms to filter out Account data based on Country and map to separate data model objects accordingly.
D. Use the data spaces feature and applying filtering on the Account data lake object based on Country.

正解：D

解説：
Data spaces are a feature that allows Data Cloud users to create subsets of data based on filters and permissions. Data spaces can be used to segregate data based on different criteria, such as geography, business unit, or product line. In this case, the consultant can use the data spaces feature and apply filtering on the Account data lake object based on Country. This way, the Data Cloud users can access only the Account data that belongs to their respective countries. References: Data Spaces, Create a Data Space

質問 # 18
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?

A. Existing measures can be removed.
B. New dimensions can be added.
C. New measures can be added.
D. Existing dimensions can be removed.

正解：B

解説：
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.

質問 # 19
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?

A. The B2C Commerce Order Bundle ingests 12 months of historical data.
B. The B2C Commerce Order Bundle does not ingest any historical data and only ingests new orders from that point on.
C. The B2C Commerce Order Bundle ingests 6 months of historical data.
D. The B2C Commerce Order Bundle ingests 30 days of historical data.

正解：B

解説：
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

質問 # 20
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