Free Salesforce Certified Platform Data Architect Plat-Arch-201 Exam Questions

Creating validation rules to check if the required attributes are entered is the best option to mandate this when customers are created in Salesforce. Validation rules allow you to specify criteria that must be met before a record can be saved. You can use validation rules to ensure that customers have a first name, last name, and email when they are created in Salesforce. This way, you can prevent incomplete or invalid data from being sent to your MDM solution.

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.

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

The correct answer is B, add custom indexes on frequently searched account and contact object fields. Custom indexes are a way to improve the performance of your queries and reports by creating indexes on specific fields that are often used in filters or joins. By adding custom indexes on frequently searched account and contact object fields, you can speed up the response time for reports and list views. Loading only the data that users are permitted to access, limiting data loading to the 2000 most recent records, or creating a skinny table are also possible solutions, but they are either not feasible, not scalable, or not supported by Salesforce.

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.

The correct answer is A, B, and D. To maintain the relationship hierarchy during migration, a data architect should use data loader to export the data from source org and then import or upsert into the target org in sequential order, create an external ID field for each object in the target org and map source record IDs to this field, and replace source record IDs with new record IDs from the target org in the import file. These steps will ensure that the records are linked correctly and the relationships are preserved. Option C is incorrect because redefining the master detail relationship fields to lookup relationship fields in the target org will change the behavior and security of the data model. Option E is incorrect because keeping the relationship fields populated with the source record IDs in the import file will cause errors and prevent the records from being imported.

The recommended solution for the Cloud Kicks Data Architect to address the requirements is to create a custom object to track shipment requests and a child custom object to track shipment items. Implement an archiving process that moves data off-platform after three years. This solution would allow Cloud Kicks to store and manage their shipment data on Salesforce, and use Salesforce reports to analyze it.However, since Cloud Kicks expects a large volume of data over time, they should implement an archiving process that moves data off-platform after three years to avoid hitting the Org data storage limit and maintain optimal performance3.External objects are not a good option for this scenario, because they are stored off-platform in an external system, such as Heroku's Postgres database, and they have limited functionality and performance compared to custom objects

Exploring external data sources in Salesforce to build 360 view of customer is the best strategy to satisfy the requirement, as it allows real-time access to data from other systems without storing it in Salesforce3. Using a customer data mart may not provide real-time information or may require additional integration efforts. Migrating customer activities from all 4 systems into Salesforce may exceed the storage limits or cause data quality issues. Periodically uploading summary information in Salesforce may not provide current or detailed information.

The data architect should recommend using field metadata attributes for compliance categorization, data owner, and data sensitivity level. This will allow the SF admins to generate reports to manage compliance based on the field metadata attributes that are defined for each data element in SF. Option A is incorrect because using metadata API to extract field attribute information and use the extract to classify and build reports will require additional development effort and may not be up-to-date with the latest changes in SF. Option C is incorrect because creating a custom object and field to capture necessary compliance information and build custom reports will require additional configuration effort and may not be consistent with the actual data elements in SF. Option D is incorrect because building reports for field information, then exporting the information to classify and report for audits will require additional manual effort and may not be accurate or timely.

Using Salesforce Bulk API in parallel mode can reduce the migration time by processing multiple batches of records simultaneously and leveraging the server resources more efficiently.The Bulk API is designed for loading large amounts of data into Salesforce

Using Bulk API to export 1 million records from Salesforce is the best option. Bulk API is a RESTful API that allows you to perform asynchronous operations on large sets of data. You can use Bulk API to create, update, delete, or query millions of records in batches. Bulk API is optimized for performance and scalability, and it can handle complex data loading scenarios.

The issue that an architect will have when implementing the quarterly accounts receivable report in Salesforce is that Salesforce does not allow more than four objects in a single report type. A report type defines the set of records and fields available to a report based on the relationships between a primary object and up to four related objects. A report type has the following limitations:

It cannot include more than four objects in a single report type, which means that the report cannot compile data from five objects (Accounts, Contacts, Opportunities, Orders, and Order Line Items) at once.

It cannot include objects that are more than two relationships away from each other, which means that the report cannot access fields from Order Line Items through Opportunities and Orders.

It cannot include objects that have a many-to-many relationship with each other, which means that the report cannot access fields from Contacts and Opportunities through the junction object Opportunity Contact Role.

Shield platform encryption is the recommended solution for encrypting sensitive patient records stored in files, as it provides encryption at rest for files and attachments, as well as standard and custom fields. Classic encryption only supports text fields with a maximum length of 175 characters, and does not encrypt files. Third-party App Exchange apps may not provide the same level of security and compliance as shield platform encryption.Storing files outside of salesforce may introduce additional complexity and latency

To recommend a clean migration, the data architect should set up a staging database, and define external IDs to merge, clean duplicate data, and load into Salesforce. This will allow the data architect to consolidate and deduplicate the data from two legacy systems before importing it into Salesforce using external IDs as unique identifiers. Option A is incorrect because defining external IDs for an object, migrating second database to first database, and loading into Salesforce will not ensure that the data is clean and duplicate-free. Option B is incorrect because defining duplicate rules in Salesforce, and loading data into Salesforce from both databases will not prevent the duplicate data from being imported into Salesforce. Option D is incorrect because defining external IDs for an object, inserting data from one database, and using upsert for a second database will not handle the duplicate data from both databases.

The correct answer is A, enable defer sharing calculations, and suspend sharing rule calculations. Defer sharing calculations and suspend sharing rule calculations are features that allow you to temporarily disable the automatic recalculation of sharing rules when you load large volumes of data. This can improve the performance and speed of your data load process by avoiding unnecessary system calculations. Loading the data through data loader, leveraging the bulk API, or enabling granular locking are also options that can help with data load times, but they do not directly address the system calculations issue.