Data-Architect Reviews Questions

 Using validation rules to mitigate this problem is the best option. Validation rules can help you prevent invalid data from being entered in your web order form. You can use validation rules to check for data quality, format, range, or consistency. For example, you can use validation rules to ensure that the order quantity is positive, the product code is valid, or the shipping address is complete.

According to the Data Modeling unit on Trailhead, some of the key actions that should be done when data modeling in Salesforce are identifying data elements, mapping legacy data, and implementing legacy data model. The unit states that “Before you start creating objects and fields in Salesforce, you need to identify the data elements that you want to store and work with. … Next, you need to map your legacy data to Salesforce objects and fields. … Finally, you need to implement your data model in Salesforce by creating custom objects and fields using declarative tools or Metadata API.” Therefore, these are the correct actions for migrating a legacy client server app to Salesforce.

Data skew occurs when a large number of child records are associated with a single parent record, or when a single user owns a large number of records. This can cause performance issues and lock contention. To avoid data skew, the data architect should limit assigning one user 10,000 records ownership, limit associating 10,000 opportunities to one account, and limit associating 10,000 records looking up to the same record

Making use of a third-party tool to help merge duplicate Contacts across Accounts and using Data.com to standardize Contact address information to help identify duplicates are two solutions that UC should implement to cleanse their data and have a single Contact across departments. A third-party tool, such as an app from the AppExchange, can provide advanced features and capabilities for finding and merging duplicate Contacts across different Accounts, based on various criteria and rules. Data.com can provide address verification and standardization services that can enhance the quality and consistency of Contact address information and make it easier to identify duplicates. The other options are not feasible or effective for cleansing the data, as they would either not work across different Accounts, not address the root cause of duplication, or not provide sufficient functionality for merging duplicates