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Salesforce Certified Data Architect Sample Questions (Q147-Q152):

NEW QUESTION # 147
Get Cloudy Consulting monitors 15,000 servers, and these servers automatically record their status every 10 minutes. Because of company policy, these status reports must be maintained for 5 years. Managers at Get Cloudy Consulting need access to up to one week's worth of these status reports with all of their details.
An Architect is recommending what data should be integrated into Salesforce and for how long it should be stored in Salesforce.
Which two limits should the Architect be aware of? (Choose two.)

A. Data storage limits
B. Webservice callout limits
C. API Request limits
D. Workflow rule limits

Answer: A,C

Explanation:
Data storage limits and API request limits are two important factors that affect the data integration and storage in Salesforce. Data storage limits determine how much data can be stored in Salesforce, and API request limits determine how many API calls can be made to Salesforce in a 24-hour period. Both of these limits depend on the edition and license type of the Salesforce org. Workflow rule limits and webservice callout limits are not directly related to data integration and storage, but rather to business logic and external services.

NEW QUESTION # 148
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?

A. Create a master detail relationship field on the Contact object.
B. Implement a Contact Conference junction object with master detail relationship to both contact and conference_c
C. Create a master detail relationship field on the Conference object.
D. Create a lookup relationship field on contact object.

Answer: B

NEW QUESTION # 149
Universal Containers (UC) has a Salesforce org with multiple automated processes defined for group membership processing, UC also has multiple admins on staff that perform manual adjustments to the role hierarchy. The automated tasks and manual tasks overlap daily, and UC is experiencing "lock errors" consistently.
What should a data architect recommend to mitigate these errors?

A. Enable sharing recalculations.
B. Enable granular locking.
C. Ask Salesforce support for additional CPU power.
D. Remove SOQL statements from Apex Loops.

Answer: B

Explanation:
Enabling granular locking (option A) is the best recommendation to mitigate these errors, as it allows finer control over how records are locked during automated or manual processes, and reduces the chances of lock contention or deadlock. Removing SOQL statements from Apex Loops (option B) is a good practice for improving performance and avoiding governor limits, but it does not directly address the lock errors issue.
Enabling sharing recalculations (option C) is also not relevant for this issue, as it is used to update sharing rules and recalculate access for records. Asking Salesforce support for additional CPU power (option D) is also not a viable solution, as it does not solve the root cause of the lock errors.

NEW QUESTION # 150
Universal Containers (UC) manages Vehicle and Service History in Salesforce. Vehicle (Vehicle__ c) and Service History (Service-History__ c) are both custom objects related through a lookup relationship.
Every week a batch synchronization process updates the Vehicle and Service History records in Salesforce. UC has two hours of migration window every week and is facing locking issues as part of the data migration process.
What should a data architect recommend to avoid locking issues without affecting performance of data migration?

A. Use Bulk API parallel mode for data migration
B. Use Bulk API serial mode for data migration
C. Insert the order in another custom object and use Batch Apex to move the records to Service_ Order__ c object.
D. Change the lookup configuration to "Clear the value of this field" when lookup record is deleted.

Answer: B

Explanation:
According to the official Salesforce guide1, using Bulk API serial mode for data migration can help avoid locking issues by processing batches in a single thread. This mode ensures that batches are processed in the order they are received and that only one batch is processed at a time. This reduces the risk of lock contention and deadlocks, especially when updating parent and child records in a lookup relationship. Option B is the correct answer because it suggests using Bulk API serial mode for data migration. Option A is incorrect because using Bulk API parallel mode for data migration can cause locking issues by processing batches in multiple threads. This mode does not guarantee the order of batch processing and can result in concurrent updates to the same records, which can lead to lock contention and deadlocks. Option C is incorrect because inserting the order in another custom object and using Batch Apex to move the records to Service_Order__c object adds unnecessary complexity and overhead to the data migration process. Option D is incorrect because changing the lookup configuration to "Clear the value of this field" when lookup record is deleted does not address the locking issues caused by data migration, but rather by record deletion.

NEW QUESTION # 151
UC has a roll-up summary field on Account to calculate the count of contacts associated with an account.
During the account load, SF is throwing an "Unable to lock a row" error.
Which solution should a data architect recommend, to resolve the error?

A. Leverage data loader platform API to load data.
B. Defer roll-up summary fields calculation during data migration.
C. Perform Batch job in serial mode and reduce batch size
D. Perform Batch job in parallel mode and reduce Batch size

Answer: C

Explanation:
The best solution to resolve the error of "Unable to lock a row" during the account load is to perform batch job in serial mode and reduce batch size. This is because roll-up summary fields are calculated synchronously when the parent record is updated, and asynchronously when the child record is updated. Therefore, updating many child records at once can cause locking issues on the parent record. To avoid this, it is recommended to use serial mode and smaller batch sizes when loading data using tools like Data Loader or Bulk API12.
Leverage data loader platform API to load data is not a good option because it does not specify the mode or batch size. Perform batch job in parallel mode and reduce batch size is not a good option because parallel mode can still cause locking issues even with smaller batches. Defer roll-up summary fields calculation during data migration is not a good option because it is not possible to defer or disable roll-up summary fields calculation

NEW QUESTION # 152
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