Salesforce Certified Data Cloud Consultant Data-Con-101 Exam Questions in PDF

Free Salesforce Data-Con-101 Dumps Questions (page: 4)

Which two steps should a consultant take if a successfully configured Amazon S3 data
stream fails to refresh with a "NO FILE FOUND" error message?

Choose 2 answers

  1. Check if correct permissions are configured for the Data Cloud user.
  2. Check if the Amazon S3 data source is enabled in Data Cloud Setup.
  3. Check If the file exists in the specified bucket location.
  4. Check if correct permissions are configured for the S3 user.

Answer(s): A,C

Explanation:

A "NO FILE FOUND" error message indicates that Data Cloud cannot access or locate the file from the Amazon S3 source. There are two possible reasons for this error and two corresponding steps that a consultant should take to troubleshoot it:

The Data Cloud user does not have the correct permissions to read the file from the Amazon S3 bucket. This could happen if the user's permission set or profile does not include the Data Cloud Data Stream Read permission, or if the user's Amazon S3 credentials are invalid or expired. To fix this issue, the consultant should check and update the user's permissions and credentials in Data Cloud and Amazon S3, respectively.

The file does not exist in the specified bucket location. This could happen if the file name or path has changed, or if the file has been deleted or moved from the Amazon S3 bucket. To fix this issue, the consultant should check and verify the file name and path in the Amazon S3 bucket, and update the data stream configuration in Data Cloud accordingly.


Reference:

Create Amazon S3 Data Stream in Data Cloud, How to Use the Amazon S3 Storage Connector in Data Cloud, Amazon S3 Connection



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

  1. Data Harmonization
  2. Unified Profiles
  3. Master Data Management
  4. Data Marketplace

Answer(s): A,B

Explanation:

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.


Reference:

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]



A retailer wants to unify profiles using Loyalty ID which is different than the unique ID of
their customers.

Which object should the consultant use in identity resolution to perform exact match rules on the

Loyalty ID?

  1. Party Identification object
  2. Loyalty Identification object
  3. Individual object
  4. Contact Identification object

Answer(s): A

Explanation:

The Party Identification object is the correct object to use in identity resolution to perform exact match rules on the Loyalty ID. The Party Identification object is a child object of the Individual object that stores different types of identifiers for an individual, such as email, phone, loyalty ID, social media handle, etc. Each identifier has a type, a value, and a source. The consultant can use the Party Identification object to create a match rule that compares the Loyalty ID type and value across different sources and links the corresponding individuals.

The other options are not correct objects to use in identity resolution to perform exact match rules on the Loyalty ID. The Loyalty Identification object does not exist in Data Cloud. The Individual object is the parent object that represents a unified profile of an individual, but it does not store the Loyalty ID directly. The Contact Identification object is a child object of the Contact object that stores identifiers for a contact, such as email, phone, etc., but it does not store the Loyalty ID.


Reference:

Data Modeling Requirements for Identity Resolution

Identity Resolution in a Data Space

Configure Identity Resolution Rulesets

Map Required Objects

Data and Identity in Data Cloud



Which data model subject area defines the revenue or quantity for an opportunity by
product family?

  1. Engagement
  2. Product
  3. Party
  4. Sales Order

Answer(s): D

Explanation:

The Sales Order subject area defines the details of an order placed by a customer for one or more products or services. It includes information such as the order date, status, amount, quantity, currency, payment method, and delivery method. The Sales Order subject area also allows you to track the revenue or quantity for an opportunity by product family, which is a grouping of products that share common characteristics or features. For example, you can use the Sales Order Line Item DMO to associate each product in an order with its product family, and then use the Sales Order Revenue DMO to calculate the total revenue or quantity for each product family in an opportunity.


Reference:

Sales Order Subject Area, Sales Order Revenue DMO Reference



Which configuration supports separate Amazon S3 buckets for data ingestion and activation?

  1. Dedicated S3 data sources in Data Cloud setup
  2. Multiple S3 connectors in Data Cloud setup
  3. Dedicated S3 data sources in activation setup
  4. Separate user credentials for data stream and activation target

Answer(s): A

Explanation:

To support separate Amazon S3 buckets for data ingestion and activation, you need to configure dedicated S3 data sources in Data Cloud setup. Data sources are used to identify the origin and type of the data that you ingest into Data Cloud1. You can create different data sources for each S3 bucket that you want to use for ingestion or activation, and specify the bucket name, region, and access credentials2. This way, you can separate and organize your data by different criteria, such as brand, region, product, or business unit3. The other options are incorrect because they do not support separate S3 buckets for data ingestion and activation. Multiple S3 connectors are not a valid configuration in Data Cloud setup, as there is only one S3 connector available4. Dedicated S3 data sources in activation setup are not a valid configuration either, as activation setup does not require data sources, but activation targets5. Separate user credentials for data stream and activation target are not sufficient to support separate S3 buckets, as you also need to specify the bucket name and region for each data source2.


Reference:

Data Sources Overview, Amazon S3 Storage Connector, Data Spaces Overview, Data Streams Overview, Data Activation Overview



A customer wants to use the transactional data from their data warehouse in Data Cloud.

They are only able to export the data via an SFTP site.

How should the file be brought into Data Cloud?

  1. Ingest the file with the SFTP Connector.
  2. Ingest the file through the Cloud Storage Connector.
  3. Manually import the file using the Data Import Wizard.
  4. Use Salesforce's Dataloader application to perform a bulk upload from a desktop.

Answer(s): A

Explanation:

The SFTP Connector is a data source connector that allows Data Cloud to ingest data from an SFTP server. The customer can use the SFTP Connector to create a data stream from their exported file and bring it into Data Cloud as a data lake object. The other options are not the best ways to bring the file into Data Cloud because:

B . The Cloud Storage Connector is a data source connector that allows Data Cloud to ingest data from cloud storage services such as Amazon S3, Azure Storage, or Google Cloud Storage. The customer does not have their data in any of these services, but only on an SFTP site.

C . The Data Import Wizard is a tool that allows users to import data for many standard Salesforce objects, such as accounts, contacts, leads, solutions, and campaign members. It is not designed to import data from an SFTP site or for custom objects in Data Cloud.

D . The Dataloader is an application that allows users to insert, update, delete, or export Salesforce records. It is not designed to ingest data from an SFTP site or into Data Cloud.


Reference:

SFTP Connector - Salesforce, Create Data Streams with the SFTP Connector in Data Cloud - Salesforce, Data Import Wizard - Salesforce, Salesforce Data Loader



When performing segmentation or activation, which time zone is used to publish and refresh data?

  1. Time zone specified on the activity at the time of creation
  2. Time zone of the user creating the activity
  3. Time zone of the Data Cloud Admin user
  4. Time zone set by the Salesforce Data Cloud org

Answer(s): 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.


Reference:

Salesforce Data Cloud Consultant Exam Guide, Segmentation, Activation



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?

  1. Data Cloud will initiate a full refresh of data from $3 and will update the formula on all records.
  2. Data Cloud will only update the formula on a go-forward basis for new records.
  3. Data Cloud does not support formula field updates for data streams of type upsert.
  4. Data Cloud will update the formula for all records at the next incremental upsert refresh.

Answer(s): A

Explanation:



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