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

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 2

A MongoDB data modeler needs to optimize a collection named orders to efficiently query documents based on the status field, which can have values like 'pending', 'completed', and 'canceled'. The collection has millions of documents, and the queries should return results quickly even under heavy load. Which of the following approaches best achieves this requirement while maintaining the collection's scalability and performance?

A : Create a separate collection for each status value and distribute the documents accordingly, querying the relevant collection based on the status.

B : Index the status field using a single field index, ensuring queries filtering by 'status' are more efficient.

C : Convert the status field into an array and use a multi-key index, ensuring multiple status values can be queried simultaneously.

D : Use a hashed index on the status field to evenly distribute the documents across the collection.

Answer: B

Question 3

A data modeler is tasked with designing a database for a movie streaming service. The database needs to efficiently store and retrieve information about movies, including the movie's title, director, genre(s), release year, and average viewer rating. How should the data modeler structure the Movie entity?

A : Model Movie as a movie's title, director, genre(s), release year, and average viewer rating.

B : Model Movie as a movie's title, director, and genre(s).

C : Model Movie as a movie's title, director, genre(s), release year, average viewer rating, and the total number of viewers.

D : Model Movie as the movie's title only.

Answer: A

Question 4

When designing a MongoDB schema for an application that tracks user activities and their corresponding locations, which approach best facilitates efficient data retrieval and updates?

A : Create a multidimensional array within each user document to store activities and their corresponding locations.

B : Store user activities and location data in separate documents within a single collection, linking them with unique identifiers.

C : Normalize all data, storing user activities in one collection and locations in another, without using any form of document references.

D : Embed user location data directly within each activity document to capitalize on document locality.

Answer: D

Question 5

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

Page: 1 / 60

Total 300 Questions | Updated On: Apr 02, 2026

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