Free MongoDB Associate-Data-Modeler Exam Questions

Become MongoDB Certified with updated Associate-Data-Modeler exam questions and correct answers

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Total 300 Questions | Updated On: Feb 09, 2026

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Question 1

In the design of a MongoDB database for an application that manages user profiles with varying degrees of completeness and privacy settings, what are the positives and negatives of relying on in-app enforcement versus schema validation to ensure data integrity and compliance with business requirements?

A : Schema validation ensures that all data writes adhere to the defined schema, reducing the need for additional application logic but lacks flexibility for handling complex conditional validation.

B : In-app enforcement is more performance-efficient because it avoids the overhead of database-level checks but can result in data integrity issues if the application crashes.

C : In-app enforcement allows for more complex logic and conditional validation but may lead to inconsistency if not implemented correctly across all application components.

D : Schema validation simplifies application code by offloading rules to the database but can lead to performance bottlenecks under heavy write loads.

Answer: C

Question 2

A data modeler is tasked with enhancing query efficiency for the salesRecords collection. Considering the queries:

db.salesRecords.find({"productId": 15}).sort({"saleDate": -1, "quantity": 1})

and

db.salesRecords.find({"saleDate": {"$gte": ISODate("2023-06-01")}}).sort({"productId": 1, "quantity": -1})

which indexing strategy would be most effective in improving response times for both queries?

A : Index on { quantity: 1, productId: 1, saleDate: -1 }

B : Index on { saleDate: -1, productId: 1, quantity: 1 }

C : Index on { productId: 1, saleDate: -1, quantity: 1 }

D : Index on { productId: 1, quantity: 1, saleDate: -1 }

Answer: C

Question 3

In designing a catalog application, a developer is dealing with Product entities that have multiple Review entities. The application frequently displays products along with the top three reviews based on ratings. How should the developer model this data to optimize for performance?

A : Use a separate collection to maintain a list of product IDs and their associated top three review IDs.

B : Embed the top three Review documents within each Product document.

C : Store each Review in a separate document, linking them to their respective Product via a product ID.

D : Embed all Review documents within their respective Product document.

Answer: B

Question 4

In an e-commerce application, the main entity Product includes details such as name, description, and price. Each Product can have multiple Review documents, which include ratings and customer comments. The application frequently displays products along with their reviews. How should the developer optimize the schema for read performance?

A : Embed Review documents within the Product document as an array of subdocuments.

B : Store each Review in a separate collection and use the Product ID to link to each Review.

C : Create a separate Review collection and a ProductReview join collection to manage the many-to-many relationship.

D : Store Review documents in a separate collection without storing a reference to the Product ID.

Answer: A

Question 5

A financial trading platform stores transaction data in MongoDB, including trade details, user portfolios, and real-time market data. The platform must efficiently process and display up-to-date portfolio valuations, historical trades, and market trends. Given the critical need for low-latency responses to support real-time decision-making and historical analysis, which MongoDB schema design pattern should be prioritized to optimize the platform's most critical data access patterns?

A : Outlier Pattern

B : Computed Pattern

C : Versioning Pattern

D : Subset Pattern

Answer: B

Page: 1 / 60

Total 300 Questions | Updated On: Feb 09, 2026

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