As part of addressing general data protection regulation (GDPR) requirements, UC plans to implement a data classification policy for all its internal systems that stores customer information including salesforce.
What should a data architect recommend so that UC can easily classify consumer information maintained in salesforce under both standard and custom objects?
A large retail B2C customer wants to build a 360 view of its customer for its call center agents. The customer interaction is currently maintained in the following system:
1. Salesforce CRM
3. Customer Master Data management (MDM)
4. Contract Management system
5. Marketing solution
What should a data architect recommend that would help upgrade uniquely identify customer across multiple systems:
Universal Containers is planning out their archiving and purging plans going forward for their custom objects Topic__c and Comment__c. Several options are being considered, including analytics snapshots, offsite storage, scheduled purges, etc. Which three questions should be considered when designing an appropriate archiving strategy?
UC is building a salesforce application to track contacts and their respective conferences that they have attended with the following requirements:
1. Contacts will be stored in the standard contact object.
2. Conferences will be stored in a custom conference_ c object.
3. Each contact may attend multiple conferences and each conference may be related to multiple contacts.
How should a data architect model the relationship between the contact and conference objects?
UC has to built a B2C ecommerce site on Heroku that shares customer and order data with a Heroku Postgres database. UC is currently utilizing Postgres as the single source of truth for both customers and orders. UC has asked a data architect to replicate the data into salesforce so that salesforce can now act as the system of record.
What are the 3 considerations that data architect should weigh before implementing this requirement? Choose 23 answers:
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