SF-Data-Arch Practice Test 2 — 30 Questions

Question 1

What is the primary architectural benefit of using 'External Objects' (Salesforce Connect) for large volumes of historical data?

Accepted Answer

To keep the local Salesforce database lean and performant.. External objects allow Salesforce to access data stored in an external system in real-time without importing it into the local database. This keeps the Salesforce storage usage low and avoids the performance impacts associated with hosting millions of records locally. It is an ideal solution for historical or secondary data that needs to be visible in the UI but does not require being in the same transactional database.

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To speed up the performance of local object triggers.

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To bypass the need for API callout security.

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To allow for complex joins between local and external objects.

Question 2

Refer to the exhibit. An architect is reviewing a JSON configuration for a data load into a Big Object. Which statement correctly describes a requirement for successfully loading data into this specific object type?

Accepted Answer

All fields defined in the Big Object's index must be present in the CSV.. Big Objects are designed for massive data storage but have unique requirements compared to standard objects. When inserting data into a Big Object, the CSV file must include all fields that are defined in the Big Object's custom index. This index is required for querying and uniquely identifying records within the Big Object store.

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The Bulk API 2.0 must be used as it is the only API supporting Big Objects.

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Triggers on the Big Object will execute for each record inserted.

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The operation must be set to 'upsert' to avoid duplicate index entries.

Question 3

Which of the following is the most important factor when choosing between the Bulk API 2.0 and the SOAP API for a large data migration?

Accepted Answer

The total number of records to be migrated.. The primary factor is the volume of data being moved. Bulk API 2.0 is designed specifically for large datasets (hundreds of thousands to millions of records) and operates asynchronously, reducing the likelihood of request timeouts. The SOAP API, while powerful for real-time transactional operations, is synchronous and poorly suited for large-scale data migrations due to its overhead and batch limitations.

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The use of OAuth authentication protocols.

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The requirement to process records synchronously.

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The availability of a command-line interface.

Question 4

Which tool should an architect select to perform a one-time migration of complex, relational data while maintaining parent-child relationships?

Accepted Answer

Salesforce Data Loader.. Salesforce Data Loader is the standard tool for managing complex data migrations. Its ability to map CSV files to objects and maintain relationships via External IDs or record IDs makes it the primary choice for data architects. Using a mature, supported tool minimizes errors during migration and ensures that data integrity is preserved across relational structures, which is critical for successful implementation projects and long-term data reliability.

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Data Import Wizard.

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Salesforce Inspector Chrome extension.

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Change Sets.

Question 5

Refer to the exhibit. What is the primary benefit of configuring a field with these settings for data integration?

Accepted Answer

It enables efficient Upsert operations.. The configuration allows the field to serve as a key for 'Upsert' operations. By marking the field as an External ID and unique, Salesforce can automatically match records from an external system to existing Salesforce records. This prevents duplicates and allows for automated, incremental data updates without needing to know the internal Salesforce record ID, which is critical for robust, scalable integration architectures.

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It enables faster reporting on the Account object.

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It allows for deduplication in the UI.

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It increases the maximum number of records.

Question 6

A financial services firm needs to load 20 million records into an object with a complex sharing model involving many Sharing Rules and Role Hierarchy levels. To minimize the time taken for the data load and avoid performance degradation, which feature should the architect utilize?

Accepted Answer

Utilizing 'Deferred Sharing Maintenance' to pause sharing rule recalculations.. Loading massive datasets into objects with complex sharing logic triggers significant overhead as Salesforce recalculates sharing access for every record. Deferring sharing calculations allows the data load to proceed without immediate recalculation, which is then performed in a single, optimized background process once the load is complete, saving hours of processing time.

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Granting 'Ignore Hierarchy' permissions to the integration user profile.

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Utilizing the 'Granular Locking' feature to allow concurrent sharing updates.

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Setting the Organization-Wide Defaults (OWD) to Public Read/Write for the load.

Question 7

Refer to the exhibit. An integration user is encountering record locking errors during high-volume data updates. What is the most effective technical solution to resolve this contention?

Accepted Answer

Group records by parent ID before processing to ensure serialization.. Record locking in Salesforce often occurs when multiple processes or threads attempt to update the same parent record or records with common children. To resolve this, the integration process should be serialized or partitioned to group related records together. By ensuring that transactions affecting the same parent record are processed sequentially in the same thread, the architecture prevents the 'Unable to lock row' errors, enhancing overall stability and throughput.

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Increase the number of threads in the integration to process records faster.

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Change the record ownership to a generic user account to avoid user locks.

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Disable the 'User Audit' tracking on the affected object.

Question 8

Universal Containers requires a data model where a Child object must have exactly one Parent object that is mandatory. If the Parent is deleted, the Child must be deleted. Which relationship should the Architect select?

Accepted Answer

Master-Detail relationship. A Master-Detail relationship creates a tight coupling where the child's lifecycle is strictly governed by the parent. Deleting the parent automatically triggers a cascade delete of all associated children. This is essential for maintaining referential integrity in parent-child hierarchies where the child cannot exist in isolation, ensuring the database remains clean and logically consistent without requiring custom automation for cleanup tasks.

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Lookup relationship

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Self-relationship

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External lookup relationship

Question 9

Which TWO strategies help manage row locking when inserting records into an object with multiple lookup relationships?

Accepted Answer

Sort the input data by the lookup field values.. High-volume loads often fail due to locking on parent records referenced by lookups. Sorting the input data by the lookup ID ensures that all children for a single parent are processed together, reducing the time a parent record remains locked. Additionally, avoiding unnecessary triggers on the parent object prevents downstream locking, significantly improving throughput for bulk data migrations.

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Use the Bulk API 2.0 in serial mode.

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Increase the batch size to 10,000.

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Convert all lookups to master-detail.

Question 10

An architect is designing a schema to store product information. Each product has many versions, and each version has many components. What is the most efficient way to model this relationship?

Accepted Answer

Model as three separate objects with Master-Detail relationships.. Creating a hierarchical relationship using lookup or master-detail fields on 'Product', 'Version', and 'Component' objects is the most scalable way to represent this structure. By isolating each layer, the architect ensures that reporting, security, and maintenance are simplified. This hierarchical model is cleaner than attempting to flatten the data, as it preserves parent-child integrity at every level.

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Flatten everything into one giant object with 100+ custom fields.

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Use a JSON field to store the hierarchy as a string.

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Create a separate object for every possible component.

Question 11

During a migration, you discover that the source system has a different date format than the required ISO 8601 format for Salesforce. What is the most efficient way to handle this?

Accepted Answer

Transform the data using an ETL tool or script before loading it into Salesforce.. Data transformation should ideally occur in the ETL (Extract, Transform, Load) layer before the data reaches Salesforce. By formatting dates during the extraction or transformation process, you ensure that the data conforms to Salesforce requirements before it hits the API. This is more scalable than attempting to force Salesforce to interpret varying formats, which can lead to data loss or import errors during the ingestion process.

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Use an Apex trigger to format the dates after the records are inserted.

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Update the Salesforce field type to 'Text' to accommodate any date format.

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Manually update the records in the Salesforce UI after the migration completes.

Question 12

What is the main advantage of using an ETL tool rather than the standard Salesforce Data Loader for a large-scale enterprise migration?

Accepted Answer

It provides visual workflow orchestration and error handling.. Enterprise ETL tools provide advanced capabilities such as graphical orchestration, error logging, automated retry logic, and seamless connectivity to heterogeneous data sources. While Data Loader is sufficient for simple, smaller loads, ETL tools allow architects to manage complex migration workflows, parallel jobs, and sophisticated data transformations across multiple systems, which is required for large-scale enterprise integration projects.

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It is always free to use.

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It bypasses Salesforce security controls.

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It allows direct database access to the Salesforce backend.

Question 13

An organization is establishing a Data Governance Council. Which THREE outcomes are primary goals of this council? (Choose Three)

Accepted Answer

Resolving data ownership and stewardship conflicts.. A Data Governance Council is a cross-functional body that aligns data strategy with business objectives. By resolving data ownership conflicts, setting enterprise-wide standards, and fostering communication between business units and IT, the council ensures that data is managed as a strategic asset. This alignment prevents silos, ensures accountability, and maximizes the value derived from data across the entire organization.

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Managing daily Apex deployment cycles.

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Directly configuring Salesforce security profiles.

Question 14

Why should an organization perform 'Data Cleansing' before migrating data into a master record system?

Accepted Answer

To remove inconsistencies and ensure data accuracy in the destination system.. Data cleansing identifies and fixes errors such as duplicates, invalid formats, and incomplete fields before they are propagated into a new system. If dirty data is ingested, it corrupts the new MDM environment, rendering reports unreliable and forcing developers to build complex, expensive workarounds. Cleaning first ensures the initial state of the master system is pristine, providing a reliable foundation for all future business operations and data-driven decisions.

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To increase the total number of records in the Salesforce database.

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To eliminate the need for any future data governance or stewardship.

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To minimize the Salesforce storage cost by deleting all inactive customer accounts.

Question 15

Refer to the exhibit. As a Data Architect, what is the governance concern if this 'VAL-099' rule remains inactive in production?

Accepted Answer

Degradation of data quality over time.. The primary concern is the uncontrolled entry of corrupt data. If a governance rule is defined but not active, the system lacks the technical enforcement to maintain quality standards. This leads to 'data rot' where the system collects invalid entries, which will eventually break downstream integrations, analytics reporting, and business processes, causing significant effort for data cleansing at a later date.

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Increased system storage limits.

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Inability to run system reports.

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Increased Apex trigger execution time.

Question 16

A Data Architect is tasked with ensuring Data Lifecycle Management is governed. Which lifecycle stage should include a requirement for automated data archiving?

Accepted Answer

Data Retention.. The 'Retention' or 'Disposition' phase is where archiving is most critical. As data ages, its value decreases, while storage costs and security risks remain. By governing this stage, the architect ensures that older data is moved to cheaper, secure storage (archiving) rather than being deleted or kept in active production tables, which optimizes system performance and maintains compliance with storage policies.

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Data Creation.

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Data Usage.

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Data Acquisition.

Question 17

A company is implementing a Customer Data Platform (CDP) to consolidate data from Salesforce, a web store, and an email marketing tool. Which TWO steps are critical for successful identity resolution?

Accepted Answer

Define deterministic and probabilistic matching rules.. Identity resolution is the process of linking data points from disparate sources to create a unified profile. By defining clear matching rules and prioritizing data attributes, the CDP can accurately identify unique individuals even when they use different identifiers across channels. This is vital for personalized marketing and accurate customer analytics, ensuring that the organization does not treat the same individual as multiple distinct records.

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Migrate all Salesforce CRM data into the marketing tool's database.

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Remove all personally identifiable information from the incoming data streams.

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Automate the deletion of all records that do not contain a phone number.

Question 18

A company is planning to migrate legacy customer data into Salesforce. Before the load, the data architect recommends data profiling. Why is this activity mandatory for a successful MDM project?

Accepted Answer

It identifies patterns, anomalies, and quality issues within the legacy data set.. Data profiling uncovers hidden quality issues, such as inconsistent formatting, missing values, or unexpected dependencies. By understanding the true state of the source data, the architect can design effective cleansing and transformation rules. Failing to profile leads to 'garbage in, garbage out,' where inaccurate data undermines the value of the new Salesforce implementation and causes significant post-migration remediation costs and user frustration.

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It ensures that the Salesforce data model is fully compatible with the legacy SQL schema.

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It increases the speed of the data load by compressing the CSV files before import.

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It automatically maps all legacy fields to the appropriate Salesforce fields without human intervention.

Question 19

A global retailer is consolidating customer master data from Salesforce, a legacy loyalty system, and an e-commerce platform. The data architect must design a matching strategy that minimizes false positives while still identifying the same customer across sources where names are spelled differently and addresses vary. Which matching approach should the architect recommend?

Accepted Answer

Probabilistic matching with a configured match threshold and score bands, supplemented by deterministic rules for high-confidence identifiers like loyalty number.. Cross-source customer matching with inconsistent names and addresses requires probabilistic matching over multiple attributes with a tuned threshold, because exact keys alone miss too many true matches. Adding deterministic rules for unique identifiers like loyalty number anchors high-confidence matches. This hybrid strategy controls false positives through scoring while preserving recall, which is exactly what the scenario demands.

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Exact matching on the combination of first name, last name, and postal code.

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Fuzzy matching on the full name field alone using a Levenshtein distance threshold.

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Deterministic matching on exact email address only, treating any non-match as a distinct customer.

Question 20

A multinational manufacturer runs a single Salesforce org for sales and service. Its governance team wants to enforce that all new custom objects created in production carry a business owner, a retention classification, and a data sensitivity label. Administrators frequently create objects ad hoc, and the team wants an automated check rather than a manual review. Which approach should the data architect recommend?

Accepted Answer

Use Metadata API and Apex Metadata API to scan object definitions against a governance checklist and block deployment when required attributes are missing.. Metadata-level governance requires inspecting object definitions, which only metadata-aware tooling can do. A programmatic check using Metadata API and Apex Metadata API lets the team compare each object against required attributes such as owner, retention classification, and sensitivity label, and it can fail the deployment automatically. Manual workflows and record-level rules cannot assert anything about the object definition itself.

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Enable Field Audit Trail and Field History Tracking on all custom objects to capture who created each object.

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Build a custom validation rule on each custom object that checks the owner field is populated on records.

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Require every administrator to submit a change request through a ServiceNow workflow before creating a custom object.