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

When optimizing a MongoDB collection's schema for a high-traffic application, what factor is crucial for determining the most effective document structure?

A : Modeling documents to reflect the application's access patterns, prioritizing query performance and data retrieval efficiency.

B : Designing documents based on the visual appeal of the JSON structure in the database management interface.

C : Ensuring all documents in a collection have a uniform size by adding placeholder data where necessary.

D : Organizing fields in alphabetical order within documents to facilitate easier indexing.

Answer: A

Question 3

A database designer is structuring a database for a book publishing company using MongoDB. In this design, there are two entities: Author and Book. An Author can write multiple Books, but each Book can be written by only one Author. What is the relationship between Authors and Books?

A : Squillions-to-one

B : One-to-one

C : One-to-many

D : Many-to-one

E : Many-to-many

Answer: C

Question 4

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 5

A team is developing a logistics application using MongoDB to track shipments in real-time. Each shipment record updates frequently with GPS coordinates, and the system requires immediate access to the latest location data for efficient routing and delivery updates. The application also needs to maintain a compact record of each shipment's path without unnecessary data duplication. Which MongoDB feature or design pattern should be used to model the shipment tracking system?

A : The Bucket Pattern, grouping location updates by day for each shipment.

B : The Preallocation Pattern, by preallocating space for each shipment document to accommodate location updates.

C : The Document Versioning Pattern, where each update creates a new version of the shipment document.

D : A standard collection with an index on the lastUpdated field.

Answer: D

Page: 1 / 60

Total 300 Questions | Updated On: Apr 02, 2026

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