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Salesforce Certified Data 360 Consultant (Data-Con-101) Data-Cloud-Consultant certification exam offers a quick way to validate skills in the market. By doing this they can upgrade their skill set and knowledge and become a certified member of the Salesforce Certified Data 360 Consultant (Data-Con-101) Data-Cloud-Consultant exam. There are several benefits of Data-Cloud-Consultant Certification that can enjoy a successful candidate for the rest of their life. Data-Cloud-Consultant also offers valid dumps book and valid dumps free download, with 365 days free updates.

Salesforce Data-Cloud-Consultant Exam Syllabus Topics:

TopicDetails
Topic 1
  • Segmentation and Insights: This topic defines basic concepts of segmentation and use cases, identifies scenarios for analyzing segment membership, configuring, refining, and maintaining segments within Data Cloud, and differentiating between calculated and streaming insights.
Topic 2
  • Data Cloud Overview: This topic covers Data Cloud's function, key terminology, business value, typical use cases, the Data Cloud lifecycle, dependencies, and principles of data ethics. These sub-topics provide an overview of Data Cloud's capabilities and applications.
Topic 3
  • Identity Resolution: It describes matching and how its rule sets are applied. Furthermore, it discusses reconciling data and its rule sets, the results of identity resolution, and use cases.

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Exam Data-Cloud-Consultant Guide & Data-Cloud-Consultant Latest Exam Answers

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Salesforce Certified Data 360 Consultant (Data-Con-101) Sample Questions (Q77-Q82):

NEW QUESTION # 77
A consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria, that are updated on a monthly basis.
What is the most efficient option to allow for this capability?

Answer: A

Explanation:
Explanation
The most efficient option to allow for this capability is to create a reusable container block with common criteria. A container block is a segment component that can bereused across multiple segments. A container block can contain any combination of filters, nested segments, and exclusion criteria. A consultant can create a container block with the exclusion criteria that apply to all the segments managed by multiple brand teams, and then add the container block to each segment. This way, the consultant can update the exclusion criteria in one place and have them reflected in all the segments that use the container block.
The other options are not the most efficient options to allow for this capability. Creating, publishing, and deploying a data kit is a way to share data and segments across different data spaces, but it does not allow for updating the exclusion criteria on a monthly basis. Creating a nested segment is a way to combine segments using logical operators, but it does not allow for excluding individuals based on specific criteria. Creating a segment and copying it for each brand is a way to create multiple segments with the same exclusion criteria, but it does not allow for updating the exclusion criteria in one place.
References:
* Create a Container Block
* Create a Segment in Data Cloud
* Create and Publish a Data Kit
* Create a Nested Segment


NEW QUESTION # 78
What does the Ignore Empty Value option do in identity resolution?

Answer: B

Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
Reference:
Data Cloud Identity Resolution Reconciliation Rule Input
Configure Identity Resolution Rulesets
Data and Identity in Data Cloud


NEW QUESTION # 79
A customer wants to create segments of users based on their Customer Lifetime Value.
However, the source data that will be brought into Data Cloud does not include that key performance indicator (KPI).
Which sequence of steps should the consultant follow to achieve this requirement?

Answer: D

Explanation:
To create segments of users based on their Customer Lifetime Value (CLV), the sequence of steps that the consultant should follow is Ingest Data > Map Data to Data Model > Create Calculated Insight > Use in Segmentation. This is because the first step is to ingest the source data into Data Cloud using data streams1. The second step is to map the source data to the data model, which defines the structure and attributes of the data2. The third step is to create a calculated insight, which is a derived attribute that is computed based on the source or unified data3. In this case, the calculated insight would be the CLV, which can be calculated using a formula or a query based on the sales order data4. The fourth step is to use the calculated insight in segmentation, which is the process of creating groups of individuals or entities based on their attributes and behaviors. By using the CLV calculated insight, the consultant can segment the users by their predicted revenue from the lifespan of their relationship with the brand. The other options are incorrect because they do not follow the correct sequence of steps to achieve the requirement. Option B is incorrect because it is not possible to create a calculated insight before ingesting and mapping the data, as the calculated insight depends on the data model objects3. Option C is incorrect because it is not possible to create a calculated insight before mapping the data, as the calculated insight depends on the data model objects3. Option D is incorrect because it is not recommended to create a calculated insight before mapping the data, as the calculated insight may not reflect the correct data model structure and attributes3. References: Data Streams Overview, Data Model Objects Overview, Calculated Insights Overview, Calculating Customer Lifetime Value (CLV) With Salesforce, [Segmentation Overview]


NEW QUESTION # 80
Data Cloud receives a nightly file of all ecommerce transactions from the previous day.
Several segments and activations depend upon calculated insights from the updated data in order to maintain accuracy in the customer's scheduled campaign messages.
What should the consultant do to ensure the ecommerce data is ready for use for each of the scheduled activations?

Answer: D

Explanation:
Explanation
The best option that the consultant should do to ensure the ecommerce data is ready for use for each of the scheduled activations is A. Use Flow to trigger a change dataevent on the ecommerce data to refresh calculated insights and segments before the activations are scheduled to run. This option allows the consultant to use the Flow feature of Data Cloud, which enables automation and orchestration of data processing tasks based on events or schedules. Flow can be used to trigger a change data event on the ecommerce data, which is a type of event that indicates that the data has been updated or changed. This event can then trigger the refresh of the calculated insights and segments that depend on the ecommerce data, ensuring that they reflect the latest data. The refresh of the calculated insights and segments can be completed before the activations are scheduled to run, ensuring that the customer's scheduled campaign messages are accurate and relevant.
The other options are not as good as option A. Option B is incorrect because setting a refresh schedule for the calculated insights to occur every hour may not be sufficient or efficient. The refresh schedule may not align with the activation schedule, resulting in outdated or inconsistent data. The refresh schedule may also consume more resources and time than necessary, as the ecommerce data may not change every hour. Option C is incorrect because ensuring the activations are set to Incremental Activation and automatically publish every hour may not solve the problem. Incremental Activation is a feature that allows only the new or changed records in a segment to be activated, reducing the activation time and size. However, this feature does not ensure that the segment data is updated or refreshed based on the ecommerce data. The activation schedule may also not match the ecommerce data update schedule, resulting in inaccurate or irrelevant campaign messages. Option D is incorrect because ensuring the segments are set to Rapid Publish and set to refresh every hour may not be optimal or effective. Rapid Publish is a feature that allows segments to be published faster by skipping some validation steps, such as checking for duplicate records or invalid values. However, this feature may compromise the quality or accuracy of the segment data, and may not be suitable for all use cases. The refresh schedule may also have the same issues as option B, as it may not sync with the ecommerce data update schedule or the activation schedule, resulting in outdated or inconsistent data. References: Salesforce Data Cloud Consultant Exam Guide, Flow, Change Data Events, Calculated Insights, Segments, [Activation]


NEW QUESTION # 81
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 # 82
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