Data-Architect Salesforce Certified Platform Data Architect (Plat-Arch-201) Free Practice Exam Questions (2025 Updated)

According to Trailhead2, one of the best practices to increase Salesforce adoption is to migrate existing data from legacy systems or spreadsheets into Salesforce, so that users can access all their data in one place and leverage the features and functionality of Salesforce. Option B is the correct answer because it suggests defining a standard mapping and training sales users to import opportunity data from Excel files into Salesforce, which can help them transition from their old process and increase their confidence and satisfaction with Salesforce. Option A is incorrect because using the Excel connector to Salesforce does not migrate the data into Salesforce, but only syncs it between Excel and Salesforce, which can cause data inconsistency and duplication issues. Option C is incorrect because loading data in an external database and providing access to it does not increase Salesforce adoption, but rather creates another system for users to manage and switch between. Option D is incorrect because creating a chatter group and uploading all Excel files to it does not migrate the data into Salesforce, but only stores it as attachments, which cannot be used for reporting or analysis purposes.

Service Cloud License (option C) is the license type that UC users need to fulfill UC’s requirements, as it allows them to track customer complaints, provide white papers on products, and provide subscription-based support. Sales Cloud License (option A) is mainly for managing sales processes and leads, Lightning Platform Starter License (option B) is for building custom apps and workflows, and Salesforce License (option D) is a generic term that does not specify a particular license type.

Enabling granular locking allows concurrent sharing rule calculations and group membership updates to run without locking each other1. This can help resolve the group membership locking issues that UC is experiencing.

 The best license type to fulfil US’s requirements is the Service Cloud license. Service Cloud licenses are designed for users who need access to customer service features, such as cases, solutions, knowledge articles, entitlements, service contracts, and service console. Service Cloud users can also access standard CRM objects, such as accounts, contacts, leads, opportunities, campaigns, and reports3. Lightning Platform Starter license is not a good option because it is intended for users who need access to one custom app and a limited set of standard objects. Salesforce license is not a specific license type, but rather a generic term for any license that grants access to the Salesforce platform. Sales Cloud license is not a good option because it is intended for users who need access to sales features, such as products, price books, quotes, orders, and forecasts.

The recommended solution to ensure long-term performance for the customer categorization process is to implement a new picklist custom field in the Account object with Gold, Silver, and Bronze values. A picklist field is a simple and efficient way to store a predefined set of values for a record. A picklist field has the following benefits:

It allows you to easily filter, sort, and group records by their category values, which can help you analyze and segment your customers.

It does not require creating any additional objects or relationships, which can reduce the data model complexity and maintenance overhead.

It supports large data volumes and can handle millions of records without affecting performance or scalability.

Implementing a Contact Conference junction object with master detail relationship to both contact and conference_c is the correct way to model the relationship between the contact and conference objects, as it allows a many-to-many relationship between them. This means that each contact can attend multiple conferences, and each conference can be related to multiple contacts. Creating a master detail relationship field on either the contact or the conference object would create a one-to-many relationship, which does not meet the requirements. Creating a lookup relationship field on contact object would also create a one-to-many relationship, and would not enforce referential integrity.

According to the Salesforce documentation2, extracting large amounts of data from Salesforce can be challenging and time-consuming, as it can encounter performance issues, API limits, timeouts, etc. To extract 100 million records from Salesforce for migration to an enterprise data warehouse (EDW), a data extraction strategy that can provide maximum performance is:

Utilize PK Chunking with the Bulk API (option C). This means using a feature that allows splitting a large query into smaller batches based on the record IDs (primary keys) of the queried object. This can improve performance and avoid timeouts by processing each batch asynchronously and in parallel using the Bulk API3.

Installing a third-party AppExchange tool (option A) is not a good solution, as it can incur additional costs and dependencies. It may also not be able to handle such a large volume of data efficiently. Calling the REST API in successive queries (option B) is also not a good solution, as it can encounter API limits and performance issues when querying such a large volume of data. Using the Bulk API in parallel mode (option D) is also not a good solution, as it can still cause timeouts and errors when querying such a large volume of data without chunking.

According to the Salesforce documentation, a relationship field is a field that allows linking one object to another object in Salesforce. There are different types of relationship fields that have different characteristics and behaviors, such as master-detail, lookup, indirect lookup, external lookup, etc.

To recommend a type of relationship field for this scenario, where legacy inventory data will be stored in a custom child object called Inventory__c, inventory data should be related to the standard Account object, the Inventory__c object should inherit the same sharing rules as the Account object, and anytime an Account record is deleted in Salesforce, the related Inventory__c record(s) should be deleted as well, a data architect should recommend:

Master-detail relationship field on Inventory__c, related to Account (option B). This means creating a field on the Inventory__c object that references the Account object as its parent. A master-detail relationship field establishes a parent-child relationship between two objects, where the parent object controls certain behaviors of the child object. For example, a master-detail relationship field can:

Inherit the sharing and security settings from the parent object to the child object. This means that the users who can access and edit the parent record can also access and edit the related child records.

Cascade delete from the parent object to the child object. This means that when a parent record is deleted, all the related child records are also deleted.

Roll up summary fields from the child object to the parent object. This means that the parent object can display aggregated information from the child records, such as count, sum, min, max, or average.

Master-detail relationship field on Account, related to Inventory__c (option A) is not a good solution, as it reverses the direction of the relationship. This means creating a field on the Account object that references the Inventory__c object as its parent. This is not possible, as a standard object cannot be on the detail side of a master-detail relationship. Indirect lookup relationship field on Account, related to Inventory__c (option C) is also not a good solution, as it is a special type of relationship field that allows linking a custom object to a standard object on an external system using an indirect reference. This is not applicable for this scenario, as both objects are in Salesforce and do not need an external reference. Lookup relationship field on Inventory__c related to Account (option D) is also not a good solution, as it establishes a looser relationship between two objects than a master-detail relationship. A lookup relationship field does not inherit sharing and security settings from the parent object to the child object, does not cascade delete from the parent object to the child object, and does not roll up summary fields from the child object to the parent object.

Using Salesforce duplicate management and using validation rules on new record create and edit are two things that an architect should consider using to maintain data quality for managing Contacts. Salesforce duplicate management allows the architect to create matching rules and duplicate rules to identify, prevent, or allow duplicate records based on various criteria. Validation rules allow the architect to enforce data quality standards and business logic by displaying error messages when users try to save invalid data. The other options are not relevant or helpful for maintaining data quality

A master data management (MDM) strategy for customer data can help UC ensure that all systems have access to the same customer information, without loading or duplicating data in all systems. An MDM strategy can also help UC avoid data conflicts and inconsistencies that may arise from having multiple systems as owners of data.

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.

Virtualizing the remaining set of data with salesforce connect and external objects is the best way to meet the requirements with minimal effort, as it allows salesforce to access data stored in Heroku Postgres without storing it in salesforce. This reduces the storage limitations and avoids data duplication. Heroku connect can bi-directionally sync data between systems, but it requires more configuration and maintenance. Making callouts to Heroku Postgres and persisting the data in salesforce may not be feasible for 1 billion records. Migrating the data to big objects may incur additional costs and require custom code to use async SOQL

According to the Salesforce documentation1, the query plan tool is a tool that can be enabled and used in the developer console to analyze the performance of a SOQL query. The query plan tool shows the cost, cardinality, sObject type, and relative cost of each query plan that Salesforce considers for a query. The relative cost indicates how expensive a query plan is compared to the Force.com query optimizer threshold. A query plan with a relative cost above 1.0 is likely to cause a time-out error.

To identify why the query is taking too long, a data architect should use the query plan tool in the developer console (option B). This way, the data architect can see which query plan is chosen by Salesforce and how it affects the performance of the query. The data architect can also use the query plan tool to optimize the query by adding indexes, filters, or limits to reduce the cost and improve the efficiency of the query.

Using Splunk to query the system logs looking for transaction time and CPU usage (option A) is not a good solution, as it can be complex, costly, and difficult to integrate with Salesforce. It may also not provide enough information or insights to identify and optimize the query performance. Using Salesforce’s query optimizer to analyze the query in the developer console (option C) is also not a good solution, as it is not a separate tool that can be used in the developer console. The query optimizer is a feature that runs automatically when a SOQL query is executed and chooses the best query plan based on various factors2. Opening a ticket with Salesforce support to retrieve transaction logs to be analyzed for processing time (option D) is also not a good solution, as it can be time-consuming, dependent, and inefficient. It may also not provide enough information or insights to identify and optimize the query performance.

 According to this article, big objects can store and manage massive amounts of data on the Salesforce platform. This can help UC to archive records from other objects or bring massive datasets from outside systems into a big object. According to this article, Einstein Analytics can be used to create dashboards and lenses to analyze big object data and get insights from advanced AI-driven analytics.

The best object model to configure within SF for migrating individual customers (B2C) data from legacy systems is to leverage person account object in Salesforce. Person accounts are a special type of accounts that store information about individual people by combining certain account and contact fields into a single record4. Person accounts are useful for B2C scenarios where there is no need to associate a company name with a contact. Person accounts also support standard Salesforce features and functionality, such as leads, campaigns, reports, dashboards, etc5. Leverage custom person account object in SF is not a good option because there is no such thing as a custom person account object. Leverage custom account and contact object in SF is not a good option because it would require creating and maintaining additional objects and fields that may not be necessary or compatible with standard Salesforce features. Leverage standard account and contact object in SF is not a good option because it would require filling in dummy values for the account name field, which is mandatory for standard accounts.

single-select restricted picklist with defined choices can be a way to configure customer type. The article states that picklists are fields that allow users to select one or more predefined values from a list, and restricted picklists ensure that users can only select from the defined values. This can help to limit the choices for customer type and ensure data quality.

 Creating a custom object related to the Invoice object with a picklist field for the Type allows the architect to categorize the attachments and report on them by Type. The standard Attachment object does not have a ContentType picklist field, and adding a custom picklist field to it would not be best practice.

 Using a validation rule for each field that takes the Stage into consideration is the simplest approach to handle this new requirement. A validation rule can enforce the field requirements based on the logic and criteria that you define, and display an error message when users try to save a record that does not meet the requirements. Updating the Opportunity page layout to mark these fields as required will not work because page layouts do not support conditional field requirements. Updating these Opportunity field definitions in Setup to be required will not work because it will apply to all stages and records. Writing an Apex trigger that checks each field when records are saved is not the simplest approach because it requires coding and testing

To build a custom big object to support storing more than 100 million records in Salesforce, a data architect should use Metadata API or Big Object in setup. Metadata API is an API that allows developers to create, retrieve, update, or delete metadata components in Salesforce programmatically. Big Object in setup is a user interface that allows admins to create big objects declaratively without writing code. Both tools can be used to define custom big objects and their fields, indexes, and relationships in Salesforce. Option A is incorrect because DX (Developer Experience) is a set of tools that allows developers to create and manage applications on Salesforce Platform, but it does not support creating big objects directly. Option D is incorrect because Object Manager in setup is a user interface that allows admins to create and manage standard and custom objects in Salesforce, but it does not support creating big objects declaratively.