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Salesforce Data-Con-101 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Identity Resolution: This domain explores creating unified customer profiles through matching and reconciliation processes. It covers how rule sets determine when records link together, how conflicting data is resolved, and understanding the outcomes and use cases of unified identities.
Topic 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.
Topic 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.
Topic 4
  • 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.
Topic 5
  • 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.

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Salesforce Certified Data Cloud Consultant Sample Questions (Q59-Q64):

NEW QUESTION # 59
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

Answer: B,C

Explanation:
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


NEW QUESTION # 60
Northern Trail Outfitters (NTO) is configuring an identity resolution ruleset based on Fuzzy Name and Normalized Email.
What should NTO do to ensure the best email address is activated?

Answer: D

Explanation:
NTO is using Fuzzy Name and Normalized Email as match rules to link together data from different sources into a unified individual profile. However, there might be cases where the same email address is available from more than one source, and NTO needs to decide which one to use for activation. For example, if Rachel has the same email address in Service Cloud and Marketing Cloud, but prefers to receive communications from NTO via Marketing Cloud, NTO needs to ensure that the email address from Marketing Cloud is activated. To do this, NTO can use the source priority order in activations, which allows them to rank the data sources in order of preference for activation. By placing Marketing Cloud higher than Service Cloud in the source priority order, NTO can make sure that the email address from Marketing Cloud is delivered to the activation target, such as an email campaign or a journey. This way, NTO can respect Rachel's preference and deliver a better customer experience. References: Configure Activations, Use Source Priority Order in Activations


NEW QUESTION # 61
Northern Trail Outfitters (NTO) wants to connect their B2C Commerce data with Data Cloud and bring two years of transactional history into Data Cloud.
What should NTO use to achieve this?

Answer: A

Explanation:
The B2C Commerce Starter Bundles are predefined data streams that ingest order and product data from B2C Commerce into Data Cloud. However, the starter bundles only bring in the last 90 days of data by default. To bring in two years of transactional history, NTO needs to use a custom extract from B2C Commerce that includes the historical data and configure the data stream to use the custom extract as the source. The other options are not sufficient to achieve this because:
A). B2C Commerce Starter Bundles only ingest the last 90 days of data by default.
B). Direct Sales Order entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion.
C). Direct Sales Product entity ingestion is not a supported method for connecting B2C Commerce data with Data Cloud. Data Cloud does not provide a direct-access connection for B2C Commerce data, only data ingestion. References: Create a B2C Commerce Data Bundle - Salesforce, B2C Commerce Connector - Salesforce, Salesforce B2C Commerce Pricing Plans & Costs


NEW QUESTION # 62
A consultant wants to build a new audience in Data Cloud.
Which three criteria can the consultant include when building a segment?
Choose 3 answers

Answer: A,B,C

Explanation:
A segment is a subset of individuals who meet certain criteria based on their attributes and behaviors. A consultant can use different types of criteria when building a segment in Data Cloud, such as:
Direct attributes: These are attributes that describe the characteristics of an individual, such as name, email, gender, age, etc. These attributes are stored in the Profile data model object (DMO) and can be used to filter individuals based on their profile data.
Calculated Insights: These are insights that perform calculations on data in a data space and store the results in a data extension. These insights can be used to segment individuals based on metrics or scores derived from their data, such as customer lifetime value, churn risk, loyalty tier, etc.
Related attributes: These are attributes that describe the relationships of an individual with other DMOs, such as Email, Engagement, Order, Product, etc. These attributes can be used to segment individuals based on their interactions or transactions with different entities, such as email opens, clicks, purchases, etc.
The other two options are not valid criteria for building a segment in Data Cloud. Data stream attributes are attributes that describe the streaming data that is ingested into Data Cloud from various sources, such as Marketing Cloud, Commerce Cloud, Service Cloud, etc. These attributes are not directly available for segmentation, but they can be transformed and stored in data extensions using streaming data transforms.
Streaming insights are insights that analyze streaming data in real time and trigger actions based on predefined conditions. These insights are not used for segmentation, but for activation and personalization. References: Create a Segment in Data Cloud, Use Insights in Data Cloud, Data Cloud Data Model


NEW QUESTION # 63
During a privacy law discussion with a customer, the customer indicates they need to honor requests for the right to be forgotten. The consultant determines that Consent API will solve this business need.
Which two considerations should the consultant inform the customer about?
Choose 2 answers

Answer: B,C

Explanation:
When advising a customer about using the Consent API in Salesforce to comply with requests for the right to be forgotten, the consultant should focus on two primary considerations:
Data deletion requests are submitted for Individual profiles (Answer C): The Consent API in Salesforce is designed to handle data deletion requests specifically for individual profiles. This means that when a request is made to delete data, it is targeted at the personal data associated with an individual's profile in the Salesforce system. The consultant should inform the customer that the requests must be specific to individual profiles to ensure accurate processing and compliance with privacy laws.
Data deletion requests submitted to Data Cloud are passed to all connected Salesforce clouds (Answer D):
When a data deletion request is made through the Consent API in Salesforce Data Cloud, the request is not limited to the Data Cloud alone. Instead, it propagates through all connected Salesforce clouds, such as Sales Cloud, Service Cloud, Marketing Cloud, etc. This ensures comprehensive compliance with the right to be forgotten across the entire Salesforce ecosystem. The customer should be aware that the deletion request will affect all instances of the individual's data across the connected Salesforce environments.


NEW QUESTION # 64
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