Salesforce Data-Architect Exam With Confidence Using Practice Dumps

 creating multiple similar products and distributing the skew across those products can be a way to mitigate issues related to lookup skew. The article explains that lookup skew happens when a very large number of records are associated with a single record in the lookup object, and this can cause record locking and performance issues. The article suggests creating multiple copies of the same product record and assigning different child records to each copy, so that the number of child records per parent record is reduced.

Creating a unique global customer ID for each customer and storing that in all systems for referential identity (option A), investing in a data duplicate tool to de-dupe and merge duplicate records across all systems (option C), and creating a customer master database external to Salesforce as a system of truth and syncing the customer data with all systems (option E) are the three options that a data architect should perform to resolve the issues with the customer data. Option A ensures that each customer can be uniquely identified across different systems, option C eliminates duplicate records and improves data quality, and option E provides a consistent and reliable source of customer data for all systems. Using Salesforce CDC to sync customer data across all systems (option B) is not a good option, as it does not address the duplication or inconsistency issues. Duplicating customer records across the system and providing a two-way sync of data between the systems (option D) is also not a good option, as it may create more confusion and conflicts with customer data.

Setting up a Validation Rule to prevent blank values and marking the field required in setup at the field level are two approaches that the Architect should take to ensure that the field always contains data coming from the source system. A Validation Rule can display an error message when a record is created or edited with a blank value for the field, and prevent it from being saved. Marking the field required in setup at the field level can enforce the requirement for all records, regardless of the page layout or the source system. The other options are not effective or recommended for ensuring data quality, as they would either not prevent blank values, not apply to all records, or not address the root cause of the problem