Free Salesforce Data-Architect Practice Exam with Questions & Answers | Set: 5

 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.

The recommended course of action to appropriately integrate the new Opportunity engagement system with Salesforce is to bring the stakeholders together to discuss the appropriate data strategy moving forward. This is because there may be valuable data in both systems that need to be reconciled and harmonized, and the Master Data Management (MDM) strategy may need to be revised or updated to accommodate the new system. The other options are not recommended, as they may result in data loss, inconsistency, or duplication

 Identifying a location to store archived data and using scheduled batch jobs to migrate and purge the aged data on a nightly basis can be a way to meet the requirements for an archive solution. The article provides a use case of how to use Heroku Connect, Postgres, and Salesforce Connect to archive old data, free up space in the org, and still retain the option to unarchive the data if needed. The article also explains how this solution can improve Salesforce performance and meet data retention policies.

Creating a custom lookup field on the standard Product to reference the parent record in the hierarchy is the correct way to modify the standard Product object model to support a hierarchical data structure. This allows UC to create a self-relationship on the Product object and define parent-child relationships among products.

Einstein Analytics can provide more analytical insights than native reports and dashboards by allowing users to explore data from multiple sources, create interactive visualizations, and apply AI-powered features5. AppExchange Apps can also provide more analytical insights by offering pre-built solutions or integrations with external tools that can enhance the reporting and analytics capabilities of Salesforce6.

 The best solution to make sure lead data has both profile and location information is to leverage external data providers to populate company profile and location data. This is because external data providers can enrich lead data with additional information from third-party sources, such as Dun & Bradstreet, ZoomInfo, or Clearbit. This can help improve lead quality, segmentation, and conversion. Salesforce supports integrating with external data providers using Data.com Clean or other AppExchange solutions2. Asking sales people to search for populating company profile and location data is inefficient and prone to errors. Running reports to identify records which do not have company profile and location data is useful, but does not solve the problem of how to populate the missing data. Exporting data out of Salesforce and sending to another team to populate company profile and location data is cumbersome and time-consuming.

According to the exam guide, one of the objectives is to "describe the use cases and considerations for deferring sharing calculations"1. This implies that option A is the correct way to load large amounts of data into Salesforce without affecting performance and data integrity. Deferring sharing calculations allows the data to be loaded first and then the sharing rules to be applied later2. Option B is not correct because workflows are not recommended for calculating summary values, as they can cause performance issues and data skew3. Option C is not correct because triggers are also not recommended for calculating summary values, as they can cause governor limit errors and data inconsistency. Option D is not correct because external IDs are used to link records from different systems, not to improve data loading performance.

Implementing a Master Data Management strategy to reconcile Leads, Accounts, and Contacts is the approach that the architect should suggest so that the requirements are met for UC. A Master Data Management strategy can provide a consistent and unified view of data across multiple systems, by defining and enforcing rules for data quality, governance, and integration. A Master Data Management strategy can also handle complex scenarios where different systems have different systems of record for different entities or fields, and where data can be modified in different systems with different values. A Master Data Management strategy can also provide a consolidated data store that links referenced records across systems and enables cross-system reporting and analysis. The other options are not suitable or sufficient for meeting the requirements, as they would either not provide a consolidated data store, not handle different systems of record, or not allow data modification in different system

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.

According to the Get Started with Custom Metadata Types unit on Trailhead, one of the use cases for custom metadata types is to define custom charges for an accounting app. The unit states that “Say that your org uses a standard accounting app. You can create a custom metadata type that defines custom charges, like duties and VAT rates. Then you can write some Apex code that calculates the total amount due for each invoice by using the metadata from your custom metadata type.” Therefore, a similar approach can be used to maintain the pricing criteria for a custom pricing engine in Salesforce.