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.

To improve data quality and avoid data skew, the data architect should create a picklist field with values sorted alphabetically for tracking shipping status on opportunity. A picklist field ensures that only valid values are entered and prevents typos or variations in spelling. Sorting the values alphabetically makes it easier for users to find and select the correct value. Data skew occurs when a large number of records are owned by a single user or have a single value for a field. Creating a picklist field with a limited number of values does not cause data skew, as long as the distribution of values is balanced and not skewed towards one value.

According to the Salesforce documentation1, the "UNABLE _TO_LOCK_ROW" error occurs when a record is being updated or created, and another operation tries to access or update the same record at the same time.
This can cause lock contention and timeout issues. To resolve the error, some of the recommended solutions are:
Perform a batch job in serial mode and reduce the batch size (option B). This means running the batch job one at a time and processing fewer records per batch. This can reduce the chances of concurrent updates and lock contention on the same records.
Use the FOR UPDATE keyword to lock records in Apex code or API calls. This means explicitly locking the records that are being accessed or updated by a transaction, and preventing other transactions from modifying them until the lock is released. This can avoid conflicts and errors between concurrent operations on the same records2.
Defer rollup summary field calculation during data migration (option A). This means disabling the automatic calculation of rollup summary fields on the parent object when child records are inserted or updated. This can improve performance and avoid locking issues on the parent records. However, this option is only available for custom objects, not standard objects3.
Performing a batch job in parallel mode and reducing the batch size (option C) is not a good solution, as it can still cause lock contention and errors if multiple batches try to access or update the same records at the same time. Leveraging Data Loader's platform API to load data (option D) is also not a good solution, as it can still encounter locking issues if other operations are modifying the same records at the same time.