A consultant needs to create a data graph based on several DLOs,
Which step should the consultant take to make this work?
A. Use a data action to update the data graph with the DLO data B. Map the DLOS to DMOS and use these in the data graph. C. Map the DLOs directly to a data graph. D. Batch transform the DLOs to multiple DMOs and activate these with the data graph.
B. Map the DLOS to DMOS and use these in the data graph.
Question 72:
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?
A. Data Cloud will initiate a full refresh of data from $3 and will update the formula on all records. B. Data Cloud will only update the formula on a go-forward basis for new records. C. Data Cloud does not support formula field updates for data streams of type upsert. D. Data Cloud will update the formula for all records at the next incremental upsert refresh.
D. Data Cloud will update the formula for all records at the next incremental upsert refresh. A formula field is a field that calculates a value based on other fields or constants. When using the S3 Connector to ingest data from an Amazon S3 bucket, Data Cloud supports creating and updating formula fields on the data lake objects (DLOs) that store the data from the S3 source. However, the formula field updates are not applied immediately, but rather at the next incremental upsert refresh of the data stream. An incremental upsert refresh is a process that adds new records and updates existing records from the S3 source to the DLO based on the primary key field. Therefore, the consultant should keep in mind that the formula field updates will affect both new and existing records, but only after the next incremental upsert refresh of the data stream. The other options are incorrect because Data Cloud does not initiate a full refresh of data from S3, does not update the formula only for new records, and does support formula field updates for data streams of type upsert. References: Create a Formula Field, Amazon S3 Connection, Data Lake Object
Question 73:
A rideshare company wants to send an email to customers that provides a year-in-review with five "fun" trip statistics, such as destination, distance traveled, etc. This raw data arrives into Data Cloud and is not aggregated at source.
The company creates a segment of customers that had at least one ride in the last 365 days.
Following best practices, which solution should the consultant recommend in Data Cloud to personalize the content of the email?
A. Use a data transform to aggregate the statistics and map them to direct attributes on Individual to include in the activation. B. Create five calculated insights for the activation and add dimension filters. C. Use a data action to send each ride as an event to Marketing Cloud Engagement, then use AMP script to summarize this data in the email. D. Include related attributes in the activation for the last 365 days.
A. Use a data transform to aggregate the statistics and map them to direct attributes on Individual to include in the activation.
Question 74:
A customer notices that their consolidation rate has recently increased. They contact the consultant to ask why.
What are two likely explanations for the increase?
Choose 2 answers
A. New data sources have been added to Data Cloud that largely overlap with the existing profiles. B. Duplicates have been removed from source system data streams. C. Identity resolution rules have been removed to reduce the number of matched profiles. D. Identity resolution rules have been added to the ruleset to increase the number of matched profiles.
A. New data sources have been added to Data Cloud that largely overlap with the existing profiles. D. Identity resolution rules have been added to the ruleset to increase the number of matched profiles. The consolidation rate is a metric that measures the amount by which source profiles are combined to produce unified profiles in Data Cloud, calculated as 1 - (number of unified profiles / number of source profiles). A higher consolidation rate means that more source profiles are matched and merged into fewer unified profiles, while a lower consolidation rate means that fewer source profiles are matched and more unified profiles are created. There are two likely explanations for why the consolidation rate has recently increased for a customer: New data sources have been added to Data Cloud that largely overlap with the existing profiles. This means that the new data sources contain many profiles that are similar or identical to the profiles from the existing data sources. For example, if a customer adds a new CRM system that has the same customer records as their old CRM system, the new data source will overlap with the existing one. When Data Cloud ingests the new data source, it will use the identity resolution ruleset to match and merge the overlapping profiles into unified profiles, resulting in a higher consolidation rate. Identity resolution rules have been added to the ruleset to increase the number of matched profiles. This means that the customer has modified their identity resolution ruleset to include more match rules or more match criteria that can identify more profiles as belonging to the same individual. For example, if a customer adds a match rule that matches profiles based on email address and phone number, instead of just email address, the ruleset will be able to match more profiles that have the same email address and phone number, resulting in a higher consolidation rate. References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Configure Identity Resolution Rulesets
Question 75:
A Data Cloud consultant is evaluating the initial phase of the Data Cloud lifecycle for a company. Which action is essential to effectively begin the Data Cloud lifecycle?
A. Identify use cases and the required data sources and data quality. B. Analyze and partition the data into data spaces. C. Migrate the existing data into the Customer 360 Data Model. D. Use calculated insights determine the benefits of Data Cloud for this company.
A. Identify use cases and the required data sources and data quality.
Question 76:
Which solution provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis?
A. Automation Studio and Profile file API B. Marketing Cloud Connect API C. Marketing Cloud Data extension Data Stream D. Email Studio Starter Data Bundle
C. Marketing Cloud Data extension Data Stream The solution that provides an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis is the Marketing Cloud Data extension Data Stream. The Marketing Cloud Data extension Data Stream is a feature that allows customers to stream data from Marketing Cloud data extensions to Data Cloud data spaces. Customers can select which data extensions they want to stream, and Data Cloud will automatically create and update the corresponding data model objects (DMOs) in the data space. Customers can also map the data extension fields to the DMO attributes using a user interface or an API. The Marketing Cloud Data extension Data Stream can help customers ingest subscriber profile attributes and other data from Marketing Cloud into Data Cloud without writing any code or setting up any complex integrations. The other options are not solutions that provide an easy way to ingest Marketing Cloud subscriber profile attributes into Data Cloud on a daily basis. Automation Studio and Profile file API are tools that can be used to export data from Marketing Cloud to external systems, but they require customers to write scripts, configure file transfers, and schedule automations. Marketing Cloud Connect API is an API that can be used to access data from Marketing Cloud in other Salesforce solutions, such as Sales Cloud or Service Cloud, but it does not support streaming data to Data Cloud. Email Studio Starter Data Bundle is a data kit that contains sample data and segments for Email Studio, but it does not contain subscriber profile attributes or stream data to Data Cloud. References: 1. Marketing Cloud Data Extension Data Stream 2. Data Cloud Data Ingestion 3. [Marketing Cloud Data Extension Data Stream API] 4. [Marketing Cloud Connect API] 5. [Email Studio Starter Data Bundle]
Question 77:
A consultant is reviewing a recent activation using engagement-based related attributes but is not seeing any related attributes in their payload for the majority of their segment members.
Which two areas should the consultant review to help troubleshoot this issue? Choose 2 answers
A. The related engagement events occurred within the last 90 days. B. The activations are referencing segments that segment on profile data rather than engagement data. C. The correct path is selected for the related attributes. D. The activated profiles have a Unified Contact Point.
A. The related engagement events occurred within the last 90 days. C. The correct path is selected for the related attributes. Engagement-based related attributes are attributes that describe the interactions of a person with an email message, such as opens, clicks, unsubscribes, etc. These attributes are stored in the Engagement data model object (DMO) and can be added to an activation to send more personalized communications. However, there are some considerations and limitations when using engagement-based related attributes, such as: For engagement data, activation supports a 90-day lookback window. This means that only the attributes from the engagement events that occurred within the last 90 days are considered for activation. Any records outside of this window are not included in the activation payload. Therefore, the consultant should review the event time of the related engagement events and make sure they are within the lookback window. The correct path to the related attributes must be selected for the activation. A path is a sequence of DMOs that are connected by relationships in the data model. For example, the path from Individual to Engagement is Individual -> Email -> Engagement. The path determines which related attributes are available for activation and how they are filtered. Therefore, the consultant should review the path selection and make sure it matches the desired related attributes and filters. The other two options are not relevant for this issue. The activations can reference segments that segment on profile data rather than engagement data, as long as the activation target supports related attributes. The activated profiles do not need to have a Unified Contact Point, which is a unique identifier for a person across different data sources, to activate engagement-based related attributes. References: Add Related Attributes to an Activation, Related Attributes in Data Cloud activation have no values, Explore the Engagement Data Model Object
Question 78:
A customer is concerned that the consolidation rate displayed in the identity resolution is quite low compared to their initial estimations.
Which configuration change should a consultant consider in order to increase the consolidation rate?
A. Change reconciliation rules to Most Occurring. B. Increase the number of matching rules. C. Include additional attributes in the existing matching rules. D. Reduce the number of matching rules.
B. Increase the number of matching rules. The consolidation rate is the amount by which source profiles are combined to produce unified profiles, calculated as - (number of unified individuals / number of source individuals). For example, if you ingest 100 source records and create 80 unified profiles, your consolidation rate is 20%. To increase the consolidation rate, you need to increase the number of matches between source profiles, which can be done by adding more match rules. Match rules define the criteria for matching source profiles based on their attributes. By increasing the number of match rules, you can increase the chances of finding matches between source profiles and thus increase the consolidation rate. On the other hand, changing reconciliation rules, including additional attributes, or reducing the number of match rules can decrease the consolidation rate, as they can either reduce the number of matches or increase the number of unified profiles. References: Identity Resolution Calculated Insight: Consolidation Rates for Unified Profiles, Identity Resolution Ruleset Processing Results, Configure Identity Resolution Rulesets
Question 79:
A consultant notices that the unified individual profile is not storing the latest email address.
Which action should the consultant take to troubleshoot this issue?
A. Remove any old email addresses from Salesforce CRM. B. Check if the mapping of DLO objects is correct to Contact Point Email. C. Confirm that the reconciliation rules are correctly used. D. Verify and update the email address in the source systems if needed.
C. Confirm that the reconciliation rules are correctly used.
Question 80:
A financial services firm specializing in wealth management contacts a Data Cloud consultant with an identity resolution request. The company wants to enhance its strategy to better manage individual client profiles within family portfolios.
Family members often share addresses and sometimes phone numbers but have distinct investment preferences and financial goals. The firm aims to avoid blending individual family profiles into a single entity to maintain personalized
service and accurate financial advice.
Which identity resolution strategy should the consultant put in place?
A. Configure a single match rule with a single connected contact point based on address. B. Use multiple contact points without individual attributes in the match rules. C. Use a more restrictive design approach to ensure the match rules perform as desired. D. Configure a single match rule based on a custom identifier.
C. Use a more restrictive design approach to ensure the match rules perform as desired.
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