Salesforce Data-Cloud-Consultant Exam With Confidence Using Practice Dumps

To support separate Amazon S3 buckets for data ingestion and activation, you need to configure dedicated S3 data sources in Data Cloud setup. Data sources are used to identify the origin and type of the data that you ingest into Data Cloud1. You can create different data sources for each S3 bucket that you want to use for ingestion or activation, and specify the bucket name, region, and access credentials2. This way, you can separate and organize your data by different criteria, such as brand, region, product, or business unit3. The other options are incorrect because they do not support separate S3 buckets for data ingestion and activation. Multiple S3 connectors are not a valid configuration in Data Cloud setup, as there isonly one S3 connector available4. Dedicated S3 data sources in activation setup are not a valid configuration either, as activation setup does not require data sources, but activation targets5. Separate user credentials for data stream and activation target are not sufficient to support separate S3 buckets, as you also need to specify the bucket name and region for each data source2. References: Data Sources Overview, Amazon S3 Storage Connector, Data Spaces Overview, Data Streams Overview, Data Activation Overview

The most likely cause of this issue is that value suggestion is still processing and takes up to 24 hours to be available. Value suggestion is a feature that enables you to see suggested values for data model object (DMO) fields when creating segment filters. However, this feature needs to be enabled for each DMO field, and it can take up to 24 hours for the suggested values to appear after enabling the feature1. Therefore, if a user is not seeing suggested values from newly-modeled data, it could be that the data has not been processed yet by the value suggestion feature. References:

Use Value Suggestions in Segmentation

 Initial Data Load:For loading large volumes of historical data, such as the last 90 days of runner profiles and activity logs, bulk ingestion is the most efficient method. It allows for high-throughput data transfer.

Bulk Ingestion:Use Salesforce Data Cloud's bulk ingestion tools to load the historical data quickly and efficiently.

 Ongoing Data Synchronization:To keep the Data Cloud updated with new and modified records as they become available in the Track My Run mobile app, streaming ingestion is appropriate. It ensures near-real-time data updates.

Streaming Ingestion:Configure streaming ingestion to continuously update the Data Cloud with new and updated data from the mobile app.

 Sequence of Actions:

Step 1:Perform bulk ingestion to import the last 90 days of historical data into Data Cloud.

Step 2:Set up streaming ingestion to handle ongoing updates and new data as it becomes available.

 Best Practice:This approach ensures that the initial large data load is handled efficiently, and ongoing updates are processed in near real-time, providing the marketing department with the most up-to-date data.

 References:

Salesforce Data Cloud Ingestion Methods

Salesforce Bulk Data Ingestion

Salesforce Streaming Data Ingestion