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Universal Containers (UC) builds three Einstein Discovery models in Salesforce to predict and maximize its revenue per customer. The models are for every region UC has a business: EMEA, AMER, and APAC.
How should a consultant help UC deploy the three Einstein models to Salesforce?
In deploying Einstein Discovery models that are tailored to different regions (EMEA, AMER, and APAC), the best approach is to segment the account data by region and apply the specific model designed for each segment. This method ensures the following:
Relevance and Accuracy: Each model can be specialized to understand and predict based on regional dynamics, which may differ significantly across geographies in terms of market behavior, customer preferences, and economic conditions.
Efficiency: Deploying region-specific models avoids the dilution of predictive power that might occur if a single model were used across all regions, which could lead to less accurate predictions.
Scalability: This approach is scalable as UC can further refine each model as more regional data becomes available or as regional market conditions evolve.
A CRM Analytics consultant has been asked to bring data from an external database as well as five external Salesforce environments into CRM Analytics. Twenty-five objects have been enabled from the local Salesforce connector.
The requirements are:
* 10 objects should be enabled from an external database
* 12 objects each from three of the external Salesforce environments
* 15 objects each from the remaining two external Salesforce environments
The consultant estimates each connector will, per object, bring between 1,000 and 1 million rows of data.
Which limit will be exceeded?
In evaluating the scenario presented where multiple external sources and objects are being integrated into CRM Analytics, we need to consider the total number of enabled objects across all connections. Here's a breakdown:
10 objects from an external database
12 objects each from three external Salesforce environments, totaling 36 objects
15 objects each from two external Salesforce environments, totaling 30 objects
25 objects already enabled from the local Salesforce connector
This brings us to a total of 101 objects enabled, which may exceed typical limits on the number of objects that can be enabled in a CRM Analytics environment, depending on the specific Salesforce licensing and platform limits.
A CRM Analytics consultant is building a dashboard for Cloud Kicks that is embedded in a separate Lightning page called "Management Dashboard" using a CRM Analytics Dashboard Component. The system administrator and the contract manager should both have access. The system administrator is able to see the dashboard and the data, but the contract manager sees a blank Lightning page.
What is causing the issue?
Universal Containers plans to upload target data from an external tool to CRM Analytics so it can calculate the sales team target attainments.
The target data changes every month, so the datasets need to be updated on a monthly basis. The target data is a CSV file that contains the Salesforce ID of the sales rep, the target amount, and the month of the target. For each sales rep, the file contains a target for every month of the current year as well as all previous years.
Based on this information, which operation should a consultant use with the Analytics External Data API to upload the file?
For uploading target data that changes on a monthly basis and includes historical data (previous years' targets), the appropriate operation is 'Overwrite.' This ensures that each time the CSV file is uploaded, the existing data in the dataset is replaced with the new data. This is critical because the target data includes both current and historical data, and using 'Overwrite' will update the entire dataset while maintaining historical accuracy.
'Append' would add new data without replacing the old records, leading to duplication, and 'Update' is not suitable for completely replacing data in this context.
Universal Containers (UC) is using CRM Analytics to create two datasets.
* Dataset A: Contains a list of activities with an "activityID" dimension and a "userID" dimension
* Dataset B: Contains a list of users with a "userID" dimension
UC wants to delete all activities from Dataset A related to users in Dataset B.
How should the CRM Analytics consultant help UC achieve this?
