Salesforce Certified Data Architect Exam Dumps & Practice Test Questions

Question 1:

Universal Containers (UC) is transitioning from a custom-built CRM system to Salesforce. They plan to migrate only operational records (open and active) into Salesforce while keeping their historical records in the legacy system. However, UC wants users to have the ability to access these historical records from within Salesforce whenever needed.

Which approach should a data architect recommend to fulfill this business requirement?

A. Use real-time integration to fetch historical records into Salesforce on demand.
B. Implement a swivel chair solution requiring users to access the legacy system separately to view historical data.
C. Utilize a mashup technique to display historical records directly within Salesforce.
D. Migrate all historical data into Salesforce and delete it after one year.

Explanation:

The ideal approach to allow access to historical records stored outside Salesforce, without migrating all data, is to implement a mashup solution (Option C). Mashups enable combining data from multiple systems and displaying them seamlessly in a single interface, in this case, Salesforce. This approach meets UC’s requirement to keep historical data accessible “on-demand” without physically moving or duplicating the entire historical dataset into Salesforce.

By using mashups, Salesforce users can view legacy system data in real time, integrated visually within Salesforce screens or dashboards, preserving a smooth user experience and minimizing data duplication or storage overhead. This method also reduces complexity, cost, and the risk of Salesforce performance degradation that could occur if all historical data were imported.

Let's analyze why the other options are less suitable:

• Option A (real-time integration) involves continuously pulling data into Salesforce. While real-time sync offers freshness, importing potentially massive historical datasets into Salesforce is inefficient, expensive, and unnecessary if the data is rarely accessed.

• Option B (swivel chair solution) forces users to toggle between two systems: Salesforce and the legacy CRM. This creates workflow inefficiencies, higher training overhead, and a fragmented user experience, which contradicts the goal of seamless access.

• Option D (import all data and delete after a year) results in excessive storage costs and complicates data governance. Additionally, deleting data after a fixed time might violate compliance rules requiring longer retention.

In summary, Option C’s mashup strategy strikes the right balance—preserving historical data in the legacy system, enabling user access through Salesforce, and avoiding unnecessary data replication or complexity. This solution aligns perfectly with UC’s operational and regulatory requirements.

Question 2:

Universal Containers has 30 million case records stored in Salesforce, with the Case object containing 80 fields. Agents have reported poor report performance and timeouts when generating case reports. 

What solution should a data architect propose to improve reporting speed and reliability?

A. Ask Salesforce support to enable skinny tables for the Case object.
B. Develop reports using custom Lightning components.
C. Create a custom object to store pre-aggregated data and report from it.
D. Move case data outside Salesforce for reporting and provide external report access.

Correct Answer: A

Explanation:

When working with very large datasets like 30 million Case records and an object having 80 fields, report performance can degrade significantly, leading to slow response times and timeouts.

Option A, enabling skinny tables, is a Salesforce feature designed specifically to improve query and report performance on large objects. Skinny tables create optimized database tables containing frequently accessed fields, which reduces the amount of data Salesforce needs to scan when generating reports. This reduces query complexity and significantly improves performance without impacting data integrity.

Option B suggests building reports with custom Lightning components. While Lightning components offer flexibility for user interfaces, they don’t directly address backend data retrieval performance. Without data-level optimization, reports may still suffer from slowness due to the large data volume.

Option C involves creating a custom object to store aggregated data for reporting. This can improve performance by reducing the volume of data processed in real time. However, it requires extra development effort and ongoing maintenance to ensure aggregates are up to date. This adds complexity and may not be as efficient or scalable as skinny tables.

Option D proposes moving data off Salesforce and running reports externally. Although this could reduce load on Salesforce, it introduces challenges around data synchronization, security, and user access complexity. Salesforce is capable of handling large data sets with proper optimizations, so offloading reporting is usually a last resort.

In summary, enabling skinny tables (Option A) provides a native, supported, and effective way to optimize report performance on large Salesforce objects like Case, making it the best recommended approach.

Question 3:

A Salesforce customer requires a custom pricing engine that determines prices based on a hierarchy of factors:

• Customer’s State

• Customer’s City (if available)

• Customer’s Zip Code (if available)

The solution must allow updates to this pricing data with minimal changes to the underlying code.

What should a data architect recommend to manage this hierarchical pricing data within Salesforce?

A. Use price books to configure pricing criteria.
B. Store pricing criteria in custom metadata types.
C. Embed pricing criteria directly inside the custom pricing engine code.
D. Create a custom object to hold the pricing criteria.

Answer: B

Explanation:

When designing a custom pricing engine in Salesforce, it is critical to choose a method that supports flexibility, maintainability, and minimal code dependency, especially when pricing depends on hierarchical location data like State, City, and Zip Code.

Custom metadata types are the best fit for this use case because they allow storing configuration data separately from application logic. This means changes to pricing criteria can be made through metadata records without modifying or redeploying code. It also enables hierarchical structuring—pricing rules can be created and organized according to state, then refined by city or zip code as needed.

Another advantage is that custom metadata types can be packaged and easily migrated across environments (sandbox to production), ensuring consistency and simplifying deployment processes.

Let’s review other options:

• Price Books (A): Primarily designed to manage product pricing related to sales transactions. They do not support complex hierarchical or dynamic pricing logic based on customer location attributes. Hence, they are not suitable for this scenario.

• Embedding criteria in engine code (C): Hard-coding the pricing criteria within the pricing engine results in rigid code that must be modified and redeployed whenever changes occur. This contradicts the requirement to minimize code changes.

• Custom Object (D): While custom objects can store data, managing relationships and updates for hierarchical pricing in custom objects introduces additional complexity and overhead. Unlike custom metadata types, custom objects don’t offer native support for easy packaging and deployment of configuration data.

In summary, custom metadata types provide an elegant and scalable way to maintain hierarchical pricing criteria in Salesforce while minimizing the need for code modifications, making option B the most appropriate choice.

Question 4:

A company operating in a tightly regulated industry plans to implement Salesforce. Their Salesforce instance contains sensitive customer data, including:

• Personally Identifiable Information (PII)

• IP restrictions on profiles based on geographic locations

• Financial records accessible only by assigned sales associates

The enterprise security team requires that:

• Access be restricted to users located within specific geographies

• User activities are monitored closely

• Exporting of data from Salesforce must be prevented

Which three Salesforce Shield features should a data architect recommend to meet these security and compliance requirements? (Choose three.)

A. Use Event Monitoring to track all user activity.
B. Encrypt sensitive customer data in Salesforce.
C. Restrict sales users’ access to PII data.
D. Limit Salesforce access to users only within specific geographic regions.
E. Apply Transaction Security policies to block data exports.

Answer: A, B, E

Explanation:

Salesforce Shield provides powerful tools to help organizations meet strict regulatory requirements, focusing on data protection, access control, and activity monitoring. In this scenario, three Shield features align best with the requirements:

• Event Monitoring (A): This tool captures detailed logs of user activity within Salesforce, including logins, data access, and changes to records. It supports compliance mandates by enabling administrators to monitor user behavior and detect any suspicious activity. This comprehensive tracking meets the requirement for detailed monitoring of user actions.

• Platform Encryption (B): Salesforce Shield’s encryption capabilities secure sensitive data fields, such as PII and financial records, by storing them in an encrypted format. Only authorized users can decrypt and access this data, ensuring privacy and compliance with data protection regulations.

• Transaction Security (E): Transaction Security policies enforce real-time security rules to prevent risky actions, such as exporting data. By applying these policies, the company can block data export attempts, meeting the strict requirement to prevent unauthorized sharing or downloading of sensitive information.

Now, let's consider why the other options are less suitable:

• Restricting sales users’ access to PII (C): Controlling access to sensitive data is typically managed through Salesforce’s standard security controls, such as profiles, roles, and field-level security—not specifically through Shield. Shield enhances monitoring and encryption but doesn’t directly manage role-based access controls.

• Limiting access by geography (D): IP-based access restrictions and login policies are native Salesforce features outside the scope of Shield. While important, geographic access control is handled via network settings and login IP ranges, not Shield capabilities.

In conclusion, to satisfy the regulatory demands, the architect should recommend Event Monitoring for activity tracking, Platform Encryption for data protection, and Transaction Security policies to block data export, making A, B, and E the correct choices.

Question 5:

A company in a tightly regulated sector is preparing to deploy Salesforce. Their Salesforce data includes personally identifiable information (PII), IP restrictions based on geographic locations applied to profiles, and financial data that must remain confidential and accessible only to assigned sales representatives. Enterprise Security requires user access to be limited to certain geographic regions and demands thorough user activity monitoring. Additionally, users should be prohibited from exporting any data from Salesforce.

Which three Salesforce Shield features should a data architect recommend to fulfill these requirements? (Select three.)

A. Use event monitoring to track all user activities.
B. Encrypt sensitive customer data stored in Salesforce.
C. Block sales representatives from accessing PII data.
D. Restrict Salesforce access to users outside designated geographic regions.
E. Apply Transaction Security policies to prevent data export from Salesforce.

Explanation:

In this scenario, the organization must adhere to strict regulatory and security requirements, including protecting PII and financial data, enforcing geographic access controls, monitoring user activity, and preventing data exports.

Event Monitoring (A) is vital for compliance, as it enables detailed logging of user actions such as logins, data views, and changes. This provides the necessary visibility into who accessed what data and when, helping meet Enterprise Security’s demand for comprehensive activity tracking.

Encrypting sensitive data (B) is essential to protect critical information like PII and financial records both at rest and during transmission. Salesforce Shield’s encryption capabilities safeguard data against unauthorized access, ensuring confidentiality and compliance with privacy laws.

Transaction Security policies (E) allow real-time enforcement of security rules. These policies can block risky user actions, such as exporting or downloading sensitive information, directly addressing the customer’s requirement to prevent data exfiltration from Salesforce.

Option C involves restricting access to PII, which is important but generally managed through Salesforce’s native permissions and field-level security rather than Shield specifically. Option D relates to geographic access controls, best handled through Salesforce’s IP restrictions rather than Shield features.

Therefore, the best recommendations combine Event Monitoring for visibility, Shield Encryption for data protection, and Transaction Security policies to control data exports, fulfilling the customer’s security and compliance mandates effectively.

Question 6:

Universal Containers uses Sales Cloud for their sales team and an ERP system as the customer master database. The sales team is encountering duplicate account records and data quality issues in Salesforce.

What two solutions should a data architect recommend to address these complaints? (Select two.)

A. Create a nightly batch process to deduplicate and merge account records.
B. Integrate Salesforce with the ERP and designate ERP as the system of record.
C. Schedule a nightly synchronization job from ERP to Salesforce.
D. Deploy a deduplication solution in Salesforce and assign clear account ownership.

Explanation:

The challenge here is to resolve duplicate account records and improve overall data quality in Salesforce, where accurate and consistent customer information is crucial for the sales team’s efficiency.

Option A, running a nightly batch job to deduplicate data, might seem useful, but it is not ideal. Batch jobs address duplicates after they occur rather than preventing them. They can be prone to errors in merge logic and do not support real-time data accuracy, allowing duplicates to exist during the day, which disrupts user experience and sales operations.

Option B, integrating Salesforce with the ERP system and making the ERP the authoritative “system of record,” is a best practice. This integration ensures Salesforce reflects the most accurate and up-to-date account information originating from the ERP. By centralizing data management, discrepancies and duplicates are reduced as Salesforce inherits consistent master data, preventing conflicting updates.

Option C, a nightly sync from ERP to Salesforce, only partially solves the issue. While it keeps data updated daily, it is not real-time, potentially leading to outdated or conflicting information during the day. It also does not prevent new duplicates created in Salesforce itself.

Option D is highly effective; implementing a deduplication tool within Salesforce helps block duplicate account creation at the source, maintaining data integrity. Assigning clear account ownership ensures accountability for data quality and encourages proactive management of records.

In conclusion, integrating Salesforce with ERP as the source of truth (Option B) and applying deduplication controls alongside ownership policies in Salesforce (Option D) provide a comprehensive, proactive solution to address duplicate and data quality concerns sustainably.

Question 7:

Universal Containers (UC) uses Salesforce as their primary sales platform and has 100,000 customers growing at 10% annually. They have an on-premise web-based billing system generating over 1 million invoices yearly on a monthly billing cycle. The sales team wants to access customer account status, invoice history, and open opportunities directly within Salesforce without switching applications. 

What approach should a data architect recommend to meet this requirement?

A. Develop a Visualforce tab embedding the billing system inside an iframe.
B. Create a custom object in Salesforce and import the last 12 months of invoice data to display on the Account page.
C. Implement an Apex callout to retrieve invoice data in real time and show it as a related list on the Account record.
D. Build a mashup page that displays billing system records inside Salesforce.

Answer: C

Explanation:

The core requirement is to provide the sales team with seamless access to billing and invoice information within Salesforce, without navigating outside the platform. Given UC’s high volume of invoices—over one million per year—and a growing customer base, the solution must be scalable, efficient, and maintain data integrity without excessive duplication.

Option A, using a Visualforce page with an iframe, allows embedding the external billing system UI inside Salesforce. However, iframes often lead to poor user experience, security restrictions, and limited integration capabilities, as they simply display external web pages rather than integrating data. Additionally, the billing system might block embedding due to security policies.

Option B involves creating a custom object to hold invoice data inside Salesforce. While this gives native access, importing and storing such a large volume (1 million+ invoices annually) is not scalable, could rapidly consume Salesforce storage, and create data synchronization issues. Managing frequent updates would be complex.

Option D suggests a mashup page, which may integrate data through web services but often involves heavier maintenance, complexity, and may not provide real-time or tightly integrated experiences.

Option C — the recommended approach — involves writing an Apex callout. This lets Salesforce dynamically request invoice data from the on-premise system as needed, displaying it in a related list on the Account page. This approach eliminates data duplication, ensures up-to-date information, and maintains high performance and scalability. The callout architecture enables real-time integration, enhancing the sales team’s productivity by providing the needed data without leaving Salesforce.

Therefore, Option C is the best solution to provide real-time, scalable, and integrated access to billing and invoice data within Salesforce.

Question 8:

Universal Containers (UC) is migrating legacy inventory data into Sales Cloud, storing it in a custom child object named Inventory__c, related to the standard Account object. The Inventory__c records must inherit the same sharing rules as their parent Account, and when an Account is deleted, its related Inventory__c records should be deleted automatically. 

Which relationship type should a data architect recommend?

A. Lookup relationship field on Inventory__c linked to Account
B. Indirect lookup relationship on Account linked to Inventory__c
C. Master-detail relationship field on Inventory__c related to Account
D. Master-detail relationship field on Account related to Inventory__c

Answer: C

Explanation:

This question focuses on selecting the relationship type that supports inheritance of sharing rules and automatic deletion of related child records, which are key requirements in this migration scenario.

Master-detail relationships in Salesforce tightly link a child object to its parent. They provide two critical features relevant here: the child inherits the parent’s sharing and visibility settings, and deleting the parent record cascades deletion to its child records.

Option C is the correct choice because creating a master-detail relationship from the child object (Inventory__c) to the parent object (Account) fulfills both requirements perfectly. Inventory__c records will share the same access permissions as their Account parent, ensuring data security and consistency. Additionally, if an Account record is deleted, Salesforce automatically deletes all related Inventory__c records, maintaining referential integrity.

Option A, a lookup relationship, allows flexible linking but does not provide sharing inheritance or cascade deletion. So, if an Account is deleted, its Inventory__c children remain, which violates the requirement.

Option B involves an indirect lookup, which is mainly used to link Salesforce objects to external data sources, not for standard Salesforce custom objects, making it irrelevant here.

Option D suggests a master-detail relationship where Account is the detail (child) and Inventory__c is the master (parent), which is invalid in Salesforce. The master-detail relationship must be defined from the child to the parent object, so this setup is not allowed.

In summary, Option C is the ideal choice because it ensures Inventory__c records inherit sharing rules from Account and are deleted automatically when their parent Account is removed, satisfying the business and data integrity requirements.

Question 9:

Northern Trail Outfitters has deployed Salesforce for its sales team across the country. However, senior leadership is concerned that the executive dashboards are not providing trustworthy data for real-time decisions. Investigation revealed these data issues in Salesforce:

• Some records are missing key information.
  Incorrect entries cause certain records to be filtered out from reports.

• Duplicate records distort summary counts.

Which three recommendations should a data architect make to resolve these problems? (Choose three.)

A. Use external data providers to supplement and enhance the Salesforce data.
B. Develop a dedicated sales data warehouse with data marts to support executive dashboards.
C. Create and deploy a data-quality monitoring dashboard to identify incomplete or erroneous records.
D. Regularly export Salesforce data, clean it externally, and then re-import it for reporting purposes.
E. Utilize Salesforce’s built-in validation rules to prevent incomplete or inaccurate data entry.

Correct Answer: C, E, A

Explanation:

The challenges Northern Trail Outfitters faces reflect common data quality issues that impact dashboard accuracy and business decisions. Addressing these requires a multi-faceted approach focusing on preventing bad data entry, monitoring data health, and enriching existing data.

First, implementing a data-quality dashboard (Option C) inside Salesforce is critical. This dashboard enables ongoing monitoring of records that are incomplete or contain errors. By highlighting problematic data in real time, data stewards can quickly identify and fix issues before they affect executive reports, enhancing the reliability of dashboards.

Next, leveraging Salesforce’s validation rules (Option E) is essential. Validation rules enforce data integrity at the point of entry by blocking incomplete or incorrect information. This proactive measure stops errors from entering the system, ensuring cleaner data from the start and reducing errors caused by invalid inputs or missing fields.

Third, augmenting Salesforce data with third-party data providers (Option A) helps enrich the records and fills gaps that may be difficult to catch internally. Third-party services can provide validated, external data such as up-to-date contact info or customer demographics. This additional data enhances completeness and accuracy, supporting better insights for sales and management.

Option B, building a separate data warehouse, while useful for aggregated historical analysis, doesn’t fix real-time data quality issues inside Salesforce. Option D, exporting and cleansing data outside Salesforce, is a reactive and manual process that adds delay and complexity, undermining real-time reporting goals.

In summary, the best strategy combines real-time data monitoring, preventive validation rules, and data enrichment from reliable external sources. This comprehensive approach improves data integrity, ensuring executive dashboards are trustworthy for timely decision-making.

Question 10:

Northern Trail Outfitters has used Salesforce Sales and Service for over a decade. Recently, the marketing team noticed the rate of returned postal mail jumped from 0% to 35%, caused by inaccurate address data stored in Salesforce.

What approach should a data architect recommend to reduce the volume of returned mail?

A. Send emails to all customers requesting them to verify their mailing address and call the company if incorrect.
B. Delete contact records from Salesforce when mail is returned to avoid postal expenses.
C. Have sales representatives call every customer to confirm and update contact details.
D. Integrate a third-party data service to regularly update and verify contact information in Salesforce.

Correct Answer: D

Explanation:

Addressing a sharp increase in returned mail requires a scalable and efficient solution focused on improving the accuracy of customer contact data. Let’s review each option:

Option A relies on customers proactively responding to email requests to verify their addresses. While this engages customers, it assumes high participation and may not be sustainable or effective. Customers might ignore emails or delay responses, leaving outdated data uncorrected.

Option B suggests deleting contact records when mail is returned. This is risky and poor data management practice because returned mail can result from temporary postal issues or recent address changes. Deleting contacts could lead to loss of valuable customer relationships and sales opportunities.

Option C involves manual phone outreach by the sales team to verify contact details. While potentially accurate, this approach is extremely labor-intensive, time-consuming, and not practical for large customer bases. It consumes valuable sales resources better spent on revenue-generating activities.

Option D proposes integrating a third-party data verification and update service directly with Salesforce. This is the most efficient and scalable approach. Third-party providers specialize in address validation and correction, continuously updating contact information based on authoritative data sources such as postal services. Automating data verification helps maintain accurate mailing addresses, dramatically reducing returned mail rates.

This proactive, automated method minimizes manual effort, enhances data reliability, and saves costs associated with returned mail and lost communications. Using third-party validation aligns with best practices for data management in enterprise CRM systems and is the recommended solution for long-term success.