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| Topic |
Details |
| Topic 1 |
- Data Ingestion and Modeling: This topic covers the different transformation capabilities within Data Cloud. It includes describing processes and considerations for data ingestion from various sources, defining, mapping, and modeling data using best practices aligned with identity resolution. Lastly, it discusses using available tools to inspect and validate ingested and modeled data.
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| 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.
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| Topic 3 |
- Act on Data: This topic defines activations and their basic use cases, using attributes and related attributes, identifying and analyzing timing dependencies affecting the Data Cloud lifecycle. Additionally it focuses on troubleshooting common problems with activations, and using data actions, including their requirements and intended use cases.
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| Topic 4 |
- 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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| Topic 5 |
- Data Cloud Setup and Administration: This topic includes applying Data Cloud permissions, permission sets, org-wide settings. It describes and configures data stream types, and data bundles. Moreover, it discusses use cases for data spaces, creating data spaces, managing and administering Data Cloud using reports, dashboards, flows, packaging, data kits, diagnosing and exploring data using Data Explorer, Profile Explorer, and APIs.
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Salesforce Certified Data Cloud Consultant Sample Questions (Q114-Q119):
NEW QUESTION # 114
A client wants to bring in loyalty data from a custom object in Salesforce CRM that contains a point balance for accrued hotel points and airline points within the same record. The client wants to split these point systems into two separate records for better tracking and processing.
What should a consultant recommend in this scenario?
- A. Create a junction object in Salesforce CRM and modify the ingestion strategy.
- B. Clone the data source object.
- C. Use batch transforms to create a second data lake object.
- D. Create a data kit from the data lake object and deploy it to the same Data Cloud org.
Answer: C
Explanation:
Batch transforms are a feature that allows creating new data lake objects based on existing data lake objects and applying transformations on them. This can be useful for splitting, merging, or reshaping data to fit the data model or business requirements. In this case, the consultant can use batch transforms to create a second data lake object that contains only the airline points from the original loyalty data object. The original object can be modified to contain only the hotel points. This way, the client can have two separate records for each point system and track and process them accordingly. References: Batch Transforms, Create a Batch Transform
NEW QUESTION # 115
Which information is provided in a .csv file when activating to Amazon S3?
- A. The metadata regarding the segment definition
- B. The activated data payload
- C. The manifest of origin sources within Data Cloud
- D. An audit log showing the user who activated the segment and when it was activated
Answer: B
Explanation:
When activating to Amazon S3, the information that is provided in a .csv file is the activated data payload. The activated data payload is the data that is sent from Data Cloud to the activation target, which in this case is an Amazon S3 bucket1. The activated data payload contains the attributes and values of the individuals or entities that are included in the segment that is being activated2. The activated data payload can be used for various purposes, such as marketing, sales, service, or analytics3. The other options are incorrect because they are not provided in a .csv file when activating to Amazon S3. Option A is incorrect because an audit log is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Activation History tab4. Option C is incorrect because the metadata regarding the segment definition is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Segmentation tab5. Option D is incorrect because the manifest of origin sources within Data Cloud is not provided in a .csv file, but it can be viewed in the Data Cloud UI under the Data Sources tab. References: Data Activation Overview, Create and Activate Segments in Data Cloud, Data Activation Use Cases, View Activation History, Segmentation Overview, [Data Sources Overview]
NEW QUESTION # 116
How does identity resolution select attributes for unified individuals when there Is conflicting information in the data model?
- A. Leverages reconciliation rules
- B. Creates additional rulesets
- C. Creates additional contact points
- D. Leverages match rules
Answer: A
Explanation:
Identity resolution is the process of creating unified profiles of individuals by matching and merging data from different sources. When there is conflicting information in the data model, such as different names, addresses, or phone numbers for the same person, identity resolution leverages reconciliation rules to select the most accurate and complete attributes for the unified profile. Reconciliation rules are configurable rules that define how to resolve conflicts based on criteria such as recency, frequency, source priority, or completeness.
For example, a reconciliation rule can specify that the most recent name or the most frequent phone number should be selected for the unified profile. Reconciliation rules can be applied at the attribute level or the contact point level. References: Identity Resolution, Reconciliation Rules, Salesforce Data Cloud Exam Questions
NEW QUESTION # 117
How does Data Cloud ensure high availability and fault tolerance for customer data?
- A. By Implementing automatic data recovery procedures
- B. By limiting data access to essential personnel
- C. By using a data center with robust backups
- D. By distributing data across multiple regions and data centers
Answer: D
Explanation:
* Ensuring High Availability and Fault Tolerance:
High availability refers to systems that are continuously operational and accessible, while fault tolerance is the ability to continue functioning in the event of a failure.
Reference:
* Data Distribution Across Multiple Regions and Data Centers:
Salesforce Data Cloud ensures high availability by replicating data across multiple geographic regions and data centers. This distribution mitigates risks associated with localized failures.
If one data center goes down, data and services can continue to be served from another location, ensuring uninterrupted service.
* Benefits of Regional Data Distribution:
Redundancy: Having multiple copies of data across regions provides redundancy, which is critical for disaster recovery.
Load Balancing: Traffic can be distributed across data centers to optimize performance and reduce latency.
Regulatory Compliance: Storing data in different regions helps meet local data residency requirements.
* Implementation in Salesforce Data Cloud:
Salesforce utilizes a robust architecture involving data replication and failover mechanisms to maintain data integrity and availability.
This architecture ensures that even in the event of a regional outage, customer data remains secure and accessible.
NEW QUESTION # 118
Northern Trail Outfitters uploads new customer data to an Amazon S3 Bucket on a daily basis to be ingested in Data Cloud.
In what order should each process be run to ensure that freshly imported data is ready and available to use for any segment?
- A. Refresh Data Stream > Calculated Insight > Identity Resolution
- B. Identity Resolution > Refresh Data Stream > Calculated Insight
- C. Refresh Data Stream > Identity Resolution > Calculated Insight
- D. Calculated Insight > Refresh Data Stream > Identity Resolution
Answer: C
Explanation:
To ensure that freshly imported data from an Amazon S3 Bucket is ready and available to use for any segment, the following processes should be run in this order:
* Refresh Data Stream: This process updates the data lake objects in Data Cloud with the latest data from the source system. It can be configured to run automatically or manually, depending on the data stream settings1. Refreshing the data stream ensures that Data Cloud has the most recent and accurate data from the Amazon S3 Bucket.
* Identity Resolution: This process creates unified individual profiles by matching and consolidating source profiles from different data streams based on the identity resolution ruleset. It runs daily by default, but can be triggered manually as well2. Identity resolution ensures that Data Cloud has a single view of each customer across different data sources.
* Calculated Insight: This process performs calculations on data lake objects or CRM data and returns a result as a new data object. It can be used to create metrics or measures for segmentation or analysis purposes3. Calculated insights ensure that Data Cloud has the derived data that can be used for personalization or activation.
References:
* 1: Configure Data Stream Refresh and Frequency - Salesforce
* 2: Identity Resolution Ruleset Processing Results - Salesforce
* 3: Calculated Insights - Salesforce
NEW QUESTION # 119
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