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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:
Before replicating the data from Heroku Postgres to Salesforce, the data architect should consider the following factors:
Whether the data is a driver of key processes implemented within Salesforce. For example, if the data is used for workflows, triggers, or validation rules, it should be replicated to Salesforce.
Whether there is a tight relationship between order data and an enterprise resource planning (ERP) application. For example, if the order data needs to be synchronized with the ERP system, it should be replicated to Salesforce.
Universals Containers' system administrators have been complaining that they are not able to make changes to its users' record, including moving them to new territories without getting ''unable to lock row'' errors. This is causing the system admins to spend hours updating user records every day.
What should the data architect do to prevent the error?
Enabling granular locking (option B) is the best option to prevent the error, as it allows finer control over how records are locked during automated or manual processes, and reduces the chances of lock contention or deadlock. Reducing number of users updated concurrently (option A) is not a good option, as it may limit the productivity and efficiency of the system admins, and it does not address the root cause of the error. Analyzing Splunk query to spot offending records (option C) is also not a good option, as it may require more time and effort, and it does not provide a permanent solution for the error. Increasing CPU for the Salesforce org (option D) is also not a good option, as it may introduce additional cost and complexity, and it does not solve the root cause of the error.
Universal Containers (CU) is in the process of implementing an enterprise data warehouse (EDW). UC needs to extract 100 million records from Salesforce for migration to the EDW.
What data extraction strategy should a data architect use for maximum performance?
Installing a third-party AppExchange tool (option A) is not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle such a large volume of data efficiently. Calling the REST API in successive queries (option B) is also not a good solution, as it can encounter API limits and performance issues when querying such a large volume of data. Using the Bulk API in parallel mode (option D) is also not a good solution, as it can still cause timeouts and errors when querying such a large volume of data without chunking.
UC has one SF org (Org A) and recently acquired a secondary company with its own Salesforce org (Org B). UC has decided to keep the orgs running separately but would like to bidirectionally share opportunities between the orgs in near-real time.
Which 3 options should a data architect recommend to share data between Org A and Org B?
Choose 3 answers.
Northern Trail Outfitters (NTO) has an external product master system that syncs product and pricing information with Salesforce. Users have been complaining that they are seeing discrepancies in product and pricing information displayed on the NTO website and Salesforce.
As a data architect, which action is recommended to avoid data sync issues?
