SF-Data-Arch Large Data Volume Considerations Practice Question
When designing a system that requires frequent querying of very large objects, which approach provides the best performance while maintaining data integrity?
⚠ Common exam trap
Candidates often select standard sharing rules or caching mechanisms, missing that schema-level adjustments are required for massive data volume queries.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Implement custom indexing or Skinny tables.
Denormalization via techniques like Skinny tables or indexing is the standard way to optimize read performance for large volumes. These strategies shift the cost from query time to write time, which is usually preferable in high-volume systems where users need quick access to data. By aligning the database schema with the specific query patterns of the application, you minimize the work the database must do to return results.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Always use SOQL with complex joins across many tables.
Why it's wrong here
Complex joins are expensive in terms of processing and query time, especially when dealing with large volumes. Each additional join increases the likelihood of query timeouts and performance degradation, making this an anti-pattern for high-volume data architectures where efficiency is paramount.
- ✓
Implement custom indexing or Skinny tables.
Why this is correct
Custom indexing and Skinny tables are the most effective native ways to optimize read performance. By providing the database with direct access paths or denormalized data sets, these features allow the query optimizer to return results rapidly, avoiding the performance pitfalls of full table scans.
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Move all data to a custom object to simplify the schema.
Why it's wrong here
Moving data to a custom object does not solve the underlying problem of large data volumes. The object will still have to process queries, and if indexes are not defined correctly, performance will be just as poor as it was in the original object structure.
- ✗
Use the Salesforce REST API for all data retrieval.
Why it's wrong here
The REST API is a transport mechanism, not a database optimization tool. Regardless of the API used, if the underlying query is not optimized (e.g., missing indexes), the query itself will remain slow, and the API request will likely time out before returning any data.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Salesforce exam blueprint
This SF-Data-Arch practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SF-Data-Arch exam.