Platform Data Architect covers data modeling, MDM, Salesforce data management, governance, large data volumes, and migration. Use this sample practice set alongside Salesforce's Platform Data Architect exam guide.
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Salesforce Data Architect Certification: Free Practice Exam & Study Guide (2026)
This exam tests data modeling, large data volume strategies, and migration architecture on the Salesforce Platform. You’ll need to know when to use Big Objects, skinny tables, custom indexes, and MDM patterns for enterprise-scale orgs. The exam is 60 scored questions in 105 minutes, with a 58% pass mark, weighted towards Data Modeling/Database Design and Salesforce Data Management (25% each).
Recommended Prerequisites
We recommend completing this certification first to prepare you better.
| Official exam name and code | Salesforce Certified Platform Data Architect (Data Architect) |
|---|---|
| Questions | 60 |
| Time allotted | 105 min |
| Passing score | 58% |
| Exam fee | $400 |
| Retake fee | $200 |
| Prerequisite certifications | Recommended preparation: Salesforce Certified Platform App Builder |
| Study guide release | Summer '26 |
Salesforce Certified Platform Data Architect Exam Weightage by Section
1. Data Modeling/Database Design (25%)
25%2. Master Data Management (5%)
5%3. Salesforce Data Management (25%)
25%4. Data Governance (10%)
10%5. Large Data Volume Considerations (20%)
20%6. Data Migration (15%)
15%Exam Topics
Last updated:
Who is the Data Architect exam for?
- Data Engineers: Professionals who manage large-scale data pipelines, ETL processes, and data quality initiatives on the Salesforce Platform.
- Enterprise Architects: Architects responsible for master data management strategies, data governance, and cross-system data consistency.
- Senior Developers: Developers who design data models, write Bulk API integrations, and optimize SOQL queries for high-volume orgs.
Exam Fees & Registration
Exam Fee
$400
One-time registration fee
Retake Fee
$200
If you need to retake the exam
Comparing certs? View all Salesforce exam fees in one place →
Certification Validity
Maintenance and renewal requirements vary. Check the issuer’s current credential page for requirements that apply to you.
How to Register
Check current Salesforce Certified Platform Data Architect (Plat-Arch-201) credential and registration details with the issuer.
View official credential detailsOfficial references: Use the issuer’s current materials to confirm exam objectives, format, and fees before booking.
Official sources: Exam guide·Salesforce exam pricing·Independent exam-prep resource; details may change.
Exam Tips
- 1All four domains are 25%. Study the full outline evenly.
- 2Data Modeling: normalization, LDV, big objects, external objects.
- 3Know Identity and Access Management architect concepts (SSO, SAML, OAuth).
- 4Integration and Development Lifecycle: when to use what, and governance.
Prerequisites
- •Application Architect
- •System Architect
- •Strong data and integration experience
Focus Areas
- •Data Architecture
- •Integration Architecture
- •Identity and Access Management
- •Development Lifecycle
Study Strategy
The Data Architect cert covers data modeling, LDV, identity, integration, and development lifecycle.
Study each domain separately, then practice cross-domain scenario questions.
Review sample scenarios from CTA prep materials.
Exam Format and First-Attempt Readiness
The Salesforce Certified Platform Data Architect exam has 60 questions in 105 min, passing score 58%. Most Salesforce exams test scenario-based decisions. Focus on when to use each feature, not just terms.
- Study Data Modeling/Database Design and Salesforce Data Management first, together they carry 50% of the exam.
- Do timed question sets. Build pacing and confidence.
- Review why wrong answers are wrong. It improves scenario reasoning.
- Book the exam once your mock scores are steady at 75%+.
Is the Data Architect Exam Hard?
Is the Data Architect Exam Hard?
The Platform Data Architect exam covers data modeling, master data management, Salesforce data management, governance, large data volumes, and migration. Preparation should include the official objectives and the design trade-offs relevant to each domain.
- 60 scored questions plus up to five unscored questions.
- 105 minutes and a 58% passing score, according to Salesforce's exam guide.
- Six weighted domains cover data modeling, MDM, Salesforce data management, governance, large data volumes, and migration.
- Exam fee: US$400; retake fee: US$200, plus applicable taxes. Prerequisite: none.
Pass Rate Guidance
Book the exam when you can explain skinny tables vs. custom indexes from memory, diagram a multi-system migration load order, and choose the right MDM pattern for a given scenario.
Data Architect Exam Format Explained
Data Architect Exam Format Explained
The exam is proctored online or in-person. Here is the format:
Total Questions
60 scored questions
Time Limit
105 min
Passing Score
58%
Question Type
Multiple-choice & multiple-select
How Many Questions Are Scenario-Based?
Use the published exam objectives to guide preparation across the six weighted domains; practice explaining the trade-offs among appropriate data architecture options.
Best Way to Pass on Your First Attempt
- Know your LDV toolkit: Skinny tables, custom indexes, Async SOQL, Big Objects, and archiving strategies, know exactly when each applies and what it costs.
- Master the migration sequence: Understand parent-before-child load order, external ID upsert, Bulk API 2.0 limits, and rollback strategies for failed loads.
- Study MDM patterns: Compare approaches for golden records, attribute survivorship, data consolidation, and traceability.
- Review data governance: Consider privacy, classification, protection, stewardship, and enterprise governance requirements.
Data Architect: Key Concepts
Data Modeling: Objects, Relationships, and Big Objects
Compare standard and custom objects, external objects, and big objects against the required data model and access patterns. Big Object SOQL queries are constrained by the big object's index fields. Platform Events provide a schema-defined event mechanism. These topics align with the published data-model and large-data-volume objectives.
Master Data Management and Deduplication
MDM design considers golden records, attribute survivorship, consolidation of source data, and traceability. Salesforce Matching Rules identify possible duplicates; Duplicate Rules specify how matching records are handled. External IDs can support upsert and cross-system record matching. These topics align with the published MDM objectives.
Data Migration: Bulk API and Integration Patterns
Bulk API 2.0 is an asynchronous option for ingesting and querying large data sets; it manages ingest batches automatically. Data Loader supports SOAP, Bulk API, and Bulk API 2.0, with the API selected through its settings rather than a fixed 200-record automatic threshold. Choose a loading approach based on data volume, transformations, latency, and operational requirements.
Data Quality and Governance
Data governance covers identifying, classifying, and protecting personal and sensitive information, as well as enterprise governance practices. Validation Rules, Duplicate Rules, Matching Rules, and field-history features are platform tools to evaluate against the organization's data-quality, privacy, and audit requirements.
Large Data Volumes: Performance and Archiving
Large Data Volume (LDV) design weighs model scalability and query performance against archiving, purging, and virtualized data options. Salesforce's query optimizer decides whether an index is useful for a query; custom indexes and skinny tables address different performance needs. Use Salesforce's current platform guidance when assessing a specific workload.
Large Data Volume orgs (millions of records) need proactive design, skinny tables and indexing to keep queries selective, and archiving to Big Objects to keep active tables lean.
How to Pass the Salesforce Data Architect Exam
The Data Architect exam tests expertise in designing Salesforce data models, managing data quality, and planning data migration. Focus on relationship types, storage limits, archiving strategies, and master data management.
Advanced Data Modeling
Know when to use lookup, master-detail, hierarchical (self-referential), and external relationships. Understand junction objects, indirect lookup fields, and how relationship type affects roll-up summaries, cascade delete, and record access.
Large Data Volume (LDV) Strategies
Know how to handle LDV: skinny tables, custom indexes, selective queries, division archiving, and big objects. Understand what causes a full table scan and how to prevent query timeouts.
Data Quality & Duplicate Management
Know Duplicate Rules, Matching Rules, and how they interact. Understand how to use Data.com clean rules (legacy knowledge), field validation, and data stewardship processes for ongoing data quality.
Data Migration Architecture
Plan migration using external IDs (upsert strategy), parent-before-child load order, and the appropriate API (Bulk API for volume, REST for real-time). Understand data validation and rollback strategies.
Master Data Management
Know MDM patterns: Registry, Consolidation, and Coexistence. Understand how to implement a golden record strategy, handle conflicting records, and synchronize master data across systems.
Is the Salesforce Certified Platform Data Architect (Plat-Arch-201) Exam Hard?
DifficultyChallenging; plan about 8-16 weeks of focused prep.
Book When ReadyScore 75%+ on three timed mocks before scheduling.
Use Practice, Not DumpsOriginal practice questions build skill without risking your credential.
Exam format: 60 questions, 105 min, 58% passing score.
Salesforce Certified Platform Data Architect Practice Questions (With Explanations)
Test your knowledge with these 15 sample questions.
Question 1: An org is querying a custom object with 40 million records through a SOQL query that filters on a non-indexed custom field, and the query is timing out. What is the most appropriate fix?
Key takeaway: A custom index on the filtered field lets the query optimizer treat the filter as selective, avoiding a full table scan.
Show correct answer and explanation
Correct answer: A. Add a custom index on the filtered field so the query optimizer can use selective filtering
A custom index on the filtered field lets the query optimizer treat the filter as selective, avoiding a full table scan. Skinny tables help reporting/read-heavy joins by excluding soft-deleted rows and reducing columns, not WHERE-clause selectivity, and Big Objects don't eliminate timeouts, they trade standard query capability for scale. API limits are unrelated to query execution time.
- Big Objects support only indexed-field queries themselves and are a different storage tier, not a drop-in timeout fix for a standard custom object.
- Skinny tables improve reporting and list-view style reads by denormalizing and excluding soft-deletes; they don't make an unindexed WHERE-clause filter selective.
- API request limits govern call volume, not how long a single SOQL query is allowed to scan before timing out.
Question 2: Which consideration is critical when designing for large data volumes?
Key takeaway: Large data volumes require attention to governor limits, indexing, and query optimization.
Show correct answer and explanation
Correct answer: B. Governor limits, indexing, and query optimization
Large data volumes require attention to governor limits, indexing, and query optimization.
- 'Only field count' oversimplifies LDV design, which centers on governor limits, indexing, and query optimization, not just field count.
- 'Only page layout' is a UI concern, unrelated to large data volume performance design.
- 'Only reports' is a display concern, unrelated to the underlying data volume performance strategy.
Question 3: A team needs to load 15 million new records into a custom object overnight using Bulk API 2.0, and batches are failing with lock contention on a shared parent account record. What should the data architect recommend?
Key takeaway: Lock contention during a bulk load typically comes from multiple parallel batches updating child records under the same parent at once.
Show correct answer and explanation
Correct answer: B. Sort the load file by the parent lookup field so related child records are grouped into the same batch
Lock contention during a bulk load typically comes from multiple parallel batches updating child records under the same parent at once. Grouping related child records so they land in the same batch (or serializing the load) avoids concurrent writes under one parent. PK Chunking is for extracting/querying large existing datasets, not for solving lock contention on inserts, and it doesn't control which records land in which batch by parent.
- PK Chunking splits large SOQL query jobs by record-ID range for extraction, it does not control batch composition on an insert job or resolve parent-record lock contention.
- Disabling validation rules changes data quality enforcement, not the parallel-batch locking behavior causing the failures.
- A batch size of 1 avoids locking at the cost of making the 15-million-record load far too slow to be practical; it isn't the recommended fix for this scenario.
Question 4: Which relationship type should be used when the child must always belong to a parent?
Key takeaway: Master-Detail enforces ownership and cascade delete; child cannot exist without parent.
Show correct answer and explanation
Correct answer: B. Master-Detail
Master-Detail enforces ownership and cascade delete; child cannot exist without parent.
- Lookup relationships allow the child to exist without a parent, the opposite of what's needed here.
- External Lookup connects to external system data, not a strict parent-child requirement.
- Indirect Lookup is used for external objects matching on specific fields, not enforcing a required parent.
Question 5: What does data archiving strategy involve?
Key takeaway: Archiving involves moving historical data while preserving access and compliance.
Show correct answer and explanation
Correct answer: B. Moving historical data off-platform or to Big Objects while keeping access patterns in mind
Archiving involves moving historical data while preserving access and compliance.
- 'Only backup' undersells archiving strategy; which also considers ongoing access patterns, not just backup.
- 'Only delete' misrepresents archiving, which is about retaining accessible historical data, not deleting it outright.
- 'Only export' undersells archiving strategy, which is broader than simple export.
Question 6: What is a Big Object in Salesforce?
Key takeaway: Big Objects store high-volume historical data with optimized query patterns.
Show correct answer and explanation
Correct answer: B. A custom object optimized for high-volume, append-only historical data
Big Objects store high-volume historical data with optimized query patterns.
- A standard object doesn't have Big Object's specific high-volume, append-only optimization.
- A report type is a display configuration, not a data storage mechanism like Big Objects.
- A dashboard visualizes data, it isn't itself a storage mechanism.
Question 7: Which indexing strategy improves SOQL performance?
Key takeaway: Custom indexes on filtered fields improve query performance.
Show correct answer and explanation
Correct answer: B. Custom indexes on frequently filtered fields and standard indexed fields
Custom indexes on filtered fields improve query performance.
- 'No indexing' contradicts the fact that indexing strategy directly improves SOQL performance.
- Indexing every field is impractical and doesn't reflect the targeted, selective indexing approach that's actually recommended.
- Limiting indexing only to formula fields ignores the broader set of frequently-filtered fields that benefit from indexing.
Question 8: Two legacy systems are being consolidated into Salesforce, and the same customer record exists in both with conflicting phone numbers and different last-modified dates. Which MDM approach correctly resolves the golden record?
Key takeaway: MDM survivorship rules (most-recent-wins, source trust ranking, or field-level survivorship) are the standard mechanism for deterministically resolving conflicting attribute values into a single golden record.
Show correct answer and explanation
Correct answer: B. Apply a survivorship rule, such as most-recently-modified or source-system trust ranking, to pick the winning field value
MDM survivorship rules (most-recent-wins, source trust ranking, or field-level survivorship) are the standard mechanism for deterministically resolving conflicting attribute values into a single golden record.
- Migration order has no bearing on which source system's data is more trustworthy or current; it isn't a survivorship strategy.
- Permanently storing both conflicting values defeats the purpose of a golden record and pushes the conflict onto downstream consumers instead of resolving it.
- Discarding verified data and re-collecting it from the customer is not a data migration or MDM technique.
Question 9: Which relationship type allows a child to exist without a parent?
Key takeaway: Lookup allows optional parent; child can exist independently.
Show correct answer and explanation
Correct answer: B. Lookup
Lookup allows optional parent; child can exist independently.
- Master-Detail relationships require the parent to exist, the opposite of what's being asked.
- Junction objects use two master-detail relationships, so children still require parents in that structure.
- External Lookup connects to external system records, which is a different scenario from a standard child-without-parent case.
Question 10: What is the purpose of a soft delete strategy?
Key takeaway: Soft delete preserves data with a deleted flag for compliance.
Show correct answer and explanation
Correct answer: B. To mark records as deleted while retaining for compliance or recovery
Soft delete preserves data with a deleted flag for compliance.
- Permanently removing data is the opposite of a soft delete, which retains records.
- 'To export data only' misrepresents the purpose of soft delete, which is about retention, not export.
- 'To archive only' undersells soft delete's specific purpose around compliance and recovery.
Question 11: Which governor limit affects bulk SOQL in triggers?
Key takeaway: Synchronous limit is 100 SOQL queries per transaction.
Show correct answer and explanation
Correct answer: B. 100 SOQL queries per transaction (sync)
Synchronous limit is 100 SOQL queries per transaction.
- 'No limit' contradicts the fact that Salesforce enforces a specific SOQL governor limit.
- 'Unlimited' contradicts the fact that a specific limit (100 for synchronous) exists.
- '50 queries' understates the actual synchronous SOQL limit of 100.
Question 12: What does master data management (MDM) address?
Key takeaway: MDM ensures consistent, clean master data across systems.
Show correct answer and explanation
Correct answer: B. Single source of truth, deduplication, and data quality
MDM ensures consistent, clean master data across systems.
- 'Only reporting' undersells MDM, which is about data quality and single source of truth, not just reporting.
- 'Only archiving' misrepresents MDM's actual focus on deduplication and data quality.
- 'Only migration' misrepresents MDM's actual focus on ongoing data quality, not just migration.
Question 13: Which data type supports high-volume, append-only use cases?
Key takeaway: Big Objects are designed for append-only, high-volume data.
Show correct answer and explanation
Correct answer: B. Big Object
Big Objects are designed for append-only, high-volume data.
- A standard object doesn't have the append-only, high-volume optimization Big Objects provide.
- A custom object with triggers doesn't scale the same way as the purpose-built Big Object architecture.
- External objects connect to external data, they aren't the native high-volume append-only storage type being asked about.
Question 14: What is the benefit of using External Objects?
Key takeaway: External Objects enable querying external systems in real time.
Show correct answer and explanation
Correct answer: B. To query external data without replicating it into Salesforce
External Objects enable querying external systems in real time.
- External Objects don't replace custom objects, they serve a different purpose (querying without replication).
- External Objects aren't specifically an archiving mechanism, that's a different, distinct use case.
- External Objects aren't a reporting tool, their benefit is querying live external data without replication.
Question 15: Which consideration applies when designing for data volume growth?
Key takeaway: Data growth requires archiving, indexing, and selective queries.
Show correct answer and explanation
Correct answer: B. Archiving strategy, indexing, and query selectivity
Data growth requires archiving, indexing, and selective queries.
- Ignoring limits contradicts the core consideration needed when designing for data volume growth.
- 'Only backup' undersells the broader set of considerations (archiving, indexing, query selectivity) needed for growth planning.
- 'Only export' undersells the broader set of considerations needed for data volume growth planning.
Get the Full Plat-Arch-201 Question Bank
Most candidates book the exam after scoring 75%+ on full mocks.
If you’re planning to test this quarter, aim to complete full mocks at least 10–14 days before your exam date.
Contact us for more information on our full 60-question mock exams and a personalized study plan. Use the contact form.
Request Mock Exams & Study PlanSalesforce Certified Platform Data Architect (Plat-Arch-201) Exam FAQs
- What is covered on the Salesforce Certified Platform Data Architect (Plat-Arch-201) exam?
- The Salesforce Certified Platform Data Architect (Plat-Arch-201) exam (formerly Salesforce Certified Data Architect) covers section-wise weightage as shown above. Use the exam topics and practice questions on this page to align your study with the official outline.
- What prerequisite is required for the Platform Data Architect exam?
- Salesforce lists no prerequisite for the Platform Data Architect exam. The guide recommends Platform App Builder, Platform Developer, and Platform Developer II certifications as optional preparation, not requirements.
- How difficult is the Data Architect certification?
- The exam covers data modeling and database design, master data management, Salesforce data management, data governance, large data volume considerations, and data migration. Review the official exam guide for the complete objectives and section weights.
- Are there free practice questions for the Salesforce Certified Platform Data Architect (Plat-Arch-201) exam?
- Yes. This page includes free sample practice questions with explanations. Use them alongside the current official documentation.
- How do I prepare for the Salesforce Certified Platform Data Architect (Plat-Arch-201) certification?
- Use the exam tips, prerequisites, and study strategy on this Salesforce Certified Platform Data Architect (Plat-Arch-201) study guide (formerly Salesforce Certified Data Architect). Focus first on the highest-weighted sections, then take the sample practice questions. Schedule the exam when you consistently score well on practice tests.
Next Architect Certifications
After this architect certification, progress toward CTA or other architect domains:
Honest Cert Breakdown
Difficulty: Hard
4/5One of the four CTA domain exams. Tests large-scale data modeling, data migration, big objects, and external data integration strategy.
Salary Range
$120,000–$160,000 / year
US average for certified professionals • Updated Summer '26 • Source: Salesforce Talent Ecosystem
Is it worth it?
Mandatory on the CTA path. Also valuable standalone for architects working on complex data migration or multi-org consolidation projects.
What Each Domain Covers
Data Modeling/Database Design
Compare data model designs, platform object features, business and technical metadata, big objects, security and sharing constraints, and data-skew trade-offs.
Master Data Management
Review MDM styles, consolidation and harmonization, survivorship criteria, external reference data, canonical models, hierarchy management, and golden-record decisions.
Salesforce Data Management
Study license and object choices, consistent persistence, a single customer view, and consolidating or working across multiple Salesforce instances.
Data Governance
Review privacy-aware data models, identification and protection of sensitive information, and enterprise data-governance approaches.
Large Data Volume Considerations
Study scalable models and performance, archiving and purging plans, and when to use virtualized data.
Data Migration
Review data quality at load time, migration performance for large volumes, and Salesforce data export approaches.
10-Week Study Plan
Working Through Scenario Questions
- 1.LDV mitigation hierarchy: When performance is the problem, first check if a custom index can help. If not, consider skinny tables. If the model itself causes skew, redesign the relationship or use big objects for archiving.
- 2.MDM pattern selection: Consolidation = merge all data into Salesforce as master. Coexistence = Salesforce is one of several authoritative systems. Centralisation = Salesforce is the single hub but doesn’t own all data. Match the pattern to the business scenario described.
- 3.Data protection: Select classification, access, retention, and encryption controls according to the sensitivity of the data and applicable requirements; no single control is appropriate for every use case.
- 4.External IDs for migration: Where source-system identifiers are available and suitable, External ID fields can support upsert and relationship mapping without relying on Salesforce record IDs.
Practice-Test Benchmark
Use practice questions to check your understanding of the published objectives. Being able to explain the assumptions and trade-offs behind a design choice is a useful self-assessment.
10 Concepts Worth Reviewing
- Object relationship types and when to use lookup vs master-detail
- Three MDM patterns: consolidation, coexistence, centralisation, and when to use each
- Duplicate Management: matching rules, duplicate rules, merge workflow
- LDV: custom indexes, skinny tables, selective SOQL, EXPLAIN PLAN
- Ownership skew and lookup skew: causes, symptoms, and mitigation
- Big objects: use cases, limitations, Async SOQL for queries
- Salesforce Shield: Platform Encryption, Event Monitoring, Field Audit Trail
- Deterministic vs probabilistic encryption and searchability implications
- Bulk API 2.0: job types, serial vs parallel, ingest lifecycle
- External IDs: creating them, using upsert, relationship mapping in migration
Questions Candidates Ask
- What is the Salesforce Data Architect certification?
- The Salesforce Certified Platform Data Architect exam has 60 scored multiple-choice questions plus up to five unscored questions, 105 minutes, a 58% passing score, a US$400 registration fee and a US$200 retake fee, plus applicable taxes. Salesforce lists no prerequisite.
- What is large data volume (LDV) and why is it important?
- Large data volume (LDV) design considers data-model scalability, query performance, archiving and purging, and virtualized data options. Custom indexes and skinny tables serve different purposes and should be considered against query patterns and platform guidance.
- What is data skew in Salesforce?
- Data skew can contribute to record-locking or sharing-calculation issues. Salesforce exam objectives call out record locking, sharing calculation issues, and excessive child-to-parent relationships as considerations when avoiding skew.
- What is Salesforce Shield and when is it required?
- Salesforce Shield includes capabilities such as Platform Encryption, Event Monitoring, and Field Audit Trail. Whether a Shield feature is appropriate depends on the organization's security, audit, and compliance requirements; check current Salesforce documentation for feature availability, supported data, and retention configuration.
- How long should I study for the Data Architect exam?
- Plan for 10–12 weeks with 10–15 hours per week. Hands-on experience with SOQL query optimisation, Bulk API loading, and data model design is essential. Candidates without LDV experience should spend extra time on that section (20% of exam) as it tests trade-offs that are hard to understand without project experience.
Plan Your Next Certification
After this certification, consider: Application Architect, System Architect, or Technical Architect (CTA).
Topic Difficulty Heatmap
Which topics are a gimme vs which ones trap confident candidates. Use this to prioritise your final-week revision. These are our own topic groupings for study planning, not the official exam sections, those and their weightings are in the credential's exam guide.
| Topic | Difficulty | Study Tip |
|---|---|---|
| Data Modeling | Hard | Normalization, LDV, and data model trade-offs, scenario questions on design. |
| Master Data Management | Moderate | MDM concepts and when to use Data Cloud vs CRM, know the positioning. |
| Data Governance | Trap ⚠ | Data quality and stewardship, governance vs security is often confused. |
| Data Architecture | Hard | Architecture decisions and documentation, integration with other domains. |
| Data Integration | Moderate | ETL and replication patterns. Know the tools and limits. |
Difficulty based on analysis of common candidate errors across each exam section.
Try It Yourself
Test yourself with free Data Architect practice questions covering the six official exam domains.
Start Free Practice QuestionsFast Facts: Data Architect Focus Areas
- Data modelling decisions: Object relationships, field strategy, external IDs, data normalisation vs. denormalisation trade-offs at scale.
- Large data volume (LDV) strategy: When and how to use skinny tables, custom indexes, query optimisation, and the impact of record volume on performance.
- Master data management: Duplicate management, data governance frameworks, external system integration patterns, and data quality strategy.
Scenario Strategy: How to Approach Data Architect Questions
Practice mapping a data challenge to the relevant published objective, then compare design options against the scenario's requirements and trade-offs.
- For LDV questions: identify whether the bottleneck is SOQL performance, storage, or UI response time; each has a different solution (custom index, skinny table, or query optimisation).
- For data model questions: prefer normalised models in transactional systems; consider denormalisation only when query performance at millions of records is explicitly required.
- For MDM questions: external IDs are the key tool for upsert operations and cross-system record matching. Know when to use a single external ID vs. multiple external IDs per object.
- For migration planning: compare data quality at load time, large-volume migration performance, and export requirements before selecting tools and methods.
How to Know You’re Ready
75%+ on 3 timed full mocks before booking
The passing score is 58%. Use the published objectives to organize preparation, and practice explaining how your proposed design addresses the stated data requirements.
Large Data Volume Design Concepts
Compare these platform capabilities against the query and data requirements in a design scenario.
1. Skinny Tables vs Custom Indexes: Different Performance Tools, Different Use Cases
Skinny tables can avoid joins for supported read-only operations and are maintained by Salesforce; contact Salesforce Support to request them. Custom indexes help the query optimizer when they suit the filter and data distribution. These are distinct options, not interchangeable fixes.
2. External Objects vs Big Objects: Real-Time vs Archive
External Objects surface data held in an external system through Salesforce Connect. Big Objects support high-volume data storage and access patterns on the Salesforce platform. Select an approach based on data location, access needs, and the applicable platform capabilities.
3. Data Masking vs Field Encryption vs Classic Encryption: Three Security Layers
Field-level encryption, Shield Platform Encryption, and sandbox data masking serve different protection goals. Compare them against the data sensitivity, access needs, environment, and compliance requirements; check current Salesforce documentation for supported fields and feature behavior.
FAQs From Candidates
- What is the Salesforce Data Architect exam format?
- The Salesforce Certified Platform Data Architect exam has 60 scored multiple-choice questions plus up to five unscored questions, a 105-minute time limit, and a 58% passing score. The registration fee is US$400 and the retake fee is US$200, plus applicable taxes. Salesforce lists no prerequisite.
- What are the highest-weight Salesforce Data Architect exam sections?
- Salesforce lists six weighted domains: Data Modeling/Database Design (25%), Master Data Management (5%), Salesforce Data Management (25%), Data Governance (10%), Large Data Volume Considerations (20%), and Data Migration (15%).
- What prerequisites do I need for the Salesforce Data Architect exam?
- Salesforce lists no prerequisite. Its recommended certifications (not required) include Platform App Builder, Platform Developer, and Platform Developer II.
- What is the hardest part of the Salesforce Data Architect exam?
- The official guide does not rank domains by difficulty. Consider reviewing the full set of objectives, including scalable data models, performance, archiving and purging, and virtualized data options.
- What topics should I review for the Data Architect exam?
- Use the official exam outline to review all six domains. For large data volume topics, compare indexing, data-model design, performance, archiving, purging, and virtualized data options against the stated requirements.
- Why do most Data Architect candidates fail questions about Skinny Tables vs Custom Indexes?
- Skinny tables are Salesforce-managed read-only copies of frequently queried subsets of large objects, they speed full-table reads. Custom indexes speed lookups on specific fields in WHERE clauses. Candidates request custom indexes when they need skinny tables and vice versa. Use skinny tables when reports and queries need to scan millions of records; use custom indexes when queries filter on s...
- Why do most Data Architect candidates fail questions about External Objects vs Big Objects?
- External Objects surface data from external systems via Salesforce Connect without importing it; data stays in the source system and is queried in real time. Big Objects store massive historical volumes inside Salesforce for archival; they are write-once and have limited query capabilities (only indexed fields). Candidates recommend External Objects for large historical data, the exam expect...
- Why do most Data Architect candidates fail questions about Data Masking vs Field Encryption vs Classic Encryption?
- Classic Encryption (legacy) encrypts individual text fields using AES 128; it is visible to users with "View Encrypted Data" permission. Shield Platform Encryption encrypts data at rest at the database level using AES 256, transparent to users with access. Data Masking replaces sensitive values with synthetic data in sandbox environments. The exam tests which to apply for a given security sce...
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