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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Ingestion and Modeling | 20% | - Data ingestion from different sources into Data Cloud - Transformation capabilities (streaming and batch) - Inspect and validate ingested and modeled data - Define, map, and model data for identity resolution |
| Topic 2: Identity Resolution | 14% | - Matching and rule sets - Reconcile data and rule sets |
| Topic 3: Segmentation and Insights | 18% | - Identify scenarios for analyzing segment membership - Configure, refine, and maintain segments within Data Cloud - Identify and differentiate between calculated and streaming insights - Define basic concepts of segmentation and use cases |
| Topic 4: Data Cloud Setup and Administration | 12% | - Diagnose and explore data using Data Explorer, Profile Explorer, and APIs - Apply Data Cloud permissions, permission sets, and org-wide settings - Identify use cases for data spaces and create data spaces based on requirements - Describe and configure the available data stream types and data bundles - Manage and administer Data Cloud using reports, dashboards, flows, packaging, and data kits |
| Topic 5: Act on Data | 18% | - Identify and analyze timing dependencies affecting the Data Cloud lifecycle - Define activations and their basic use cases - Use attributes and related attributes - Troubleshoot common problems with activations - Use data actions and identify their requirements and intended use cases |
| Topic 6: Solution Overview | 18% | - Describe and apply the principles of data ethics - Articulate how Data Cloud works and its dependencies - Identify typical use cases for Data Cloud - Describe Data Cloud's function, key terminology, and business value |
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NEW QUESTION # 27
An analyst from Cloud Kicks needs to get quick Insights to determine the average sales per day during the past week.
What should a consultant recommend?
Answer: C
Explanation:
To help the analyst from Cloud Kicks determine the average sales per day during the past week, Salesforce Reports is the most efficient and straightforward solution. Here's a detailed breakdown:
Understanding Salesforce Reports :Salesforce Reports is a native tool within the Salesforce platform that allows users to create, customize, and analyze data in various formats. It is particularly well-suited for quick insights and ad-hoc analysis without requiring complex development or integrations.
Why Not Other Options?
Option A (Salesforce Flows) : While Salesforce Flows is a powerful automation tool, it is not designed for analytical purposes. Creating a flow to calculate average sales per day would require additional configuration and logic, making it unnecessarily complex for this use case.
Option B (Lightning Web Component Utilizing Query API) : Using a Lightning Web Component with the Query API involves custom development. While this approach is flexible, it is overkill for a simple analytical task like calculating average sales.
Option D (Segment Activation to Azure) : Segment activation refers to exporting segmented customer data to external platforms like Azure. This process is unrelated to generating quick insights and would introduce unnecessary complexity for this requirement.
How Salesforce Reports Can Be Used :
Step 1: Create a Report : Navigate to the Salesforce Reports tab and create a new report based on the relevant object (e.g., Opportunities or Orders).
Step 2: Filter by Date Range : Apply a filter to include only records from the past week. For example, set the
"Close Date" field to "Last Week."
Step 3: Add Summary Fields : Use summary formulas or grouping to calculate total sales for each day. Then, compute the average sales per day by dividing the total sales by the number of days in the range.
Step 4: Run the Report : Execute the report to view the results instantly.
Salesforce Documentation Reference :Salesforce's official documentation highlights that Reports are the go-to tool for analyzing and summarizing data quickly. They are designed to provide actionable insights without requiring advanced technical skills, making them ideal for tasks like calculating average sales.
By leveraging Salesforce Reports, the analyst can efficiently obtain the required insights without additional development or integration efforts.
NEW QUESTION # 28
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?
Answer: A
NEW QUESTION # 29
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
Answer: C,D
Explanation:
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
NEW QUESTION # 30
A customer is trying to activate data from Data Cloud to an Amazon S3 Cloud File Storage Bucket.
Which authentication type should the consultant recommend to connect to the S3 bucket from Data Cloud?
Answer: A
NEW QUESTION # 31
An organization wants to enable users with the ability to identify and select text attributes from a picklist of options.
Which Data Cloud feature should help with this use case?
Answer: A
Explanation:
Value suggestion is a Data Cloud feature that allows users to see and select the possible values for a text field when creating segment filters. Value suggestion can be enabled or disabled for each data model object (DMO) field in the DMO record home. Value suggestion can help users to identify and select text attributes from a picklist of options, without having to type or remember the exact values. Value suggestion can also reduce errors and improve data quality by ensuring consistent and valid values for the segment filters. References: Use Value Suggestions in Segmentation, Considerations for Selecting Related Attributes
NEW QUESTION # 32
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