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: Apr 02, 2026

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Question 1

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 2

Regarding MongoDB schema design and document structure, which two of the following statements are accurate?

A : All documents within a collection must have the same fields and data types.

B : Embedding documents is recommended for frequently accessed data that is read together.

C : Schema validation rules are enforced by default on all collections upon creation.

D : Denormalization can reduce the need for expensive joins and improve read performance.

Answer: B,D

Question 3

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 4

A MongoDB data modeler is designing a schema for a content management system (CMS) that stores articles, each with multiple tags and categories. The CMS will feature frequent searches by tags and categories, with more read operations than writes. The schema must optimize for query performance and scalability. What schema design pattern is most appropriate for this use case?

A : Use a separate collection for tags and categories, with references in the article documents.

B : Implement a Bucket Pattern, grouping articles by tags and categories in the same document.

C : Utilize the Polymorphic Pattern, allowing tags and categories to adapt to different types of articles.

D : Embed tags and categories directly within each article document.

Answer: D

Question 5

In MongoDB, how should the analysis of query and analytics patterns influence the decision on indexing strategies, particularly with respect to the operational context of queries being part of a transaction?

A : Indexes should be avoided in transactional queries to reduce the complexity of transactions and improve write performance.

B : For queries within transactions, prioritize the creation of indexes on fields involved in the read operations of the transaction to minimize locking and improve concurrency.

C : Ensure that every transactional query operation utilizes a hashed index to guarantee performance efficiency across all transaction phases.

D : Use single field indexes for all fields involved in transactional queries to maximize the flexibility of query optimization.

Answer: B

Page: 1 / 60

Total 300 Questions | Updated On: Apr 02, 2026

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