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

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 2

A developer is building a project management tool where each Project can have multiple Task entities. The tasks are frequently updated and accessed together with their parent project. What is the most efficient way to model this data relationship in MongoDB to optimize for task read and write operations?

A : Embed Task documents as an array of subdocuments within each Project.

B : Create a separate collection for tasks and projects, linking them through a shared projectId and taskId in a third collection.

C : Store each Task in a separate collection, with a projectId to reference back to their Project.

Answer: A

Question 3

In MongoDB schema design, what is a critical implication to consider when adding another piece of data into an array field, especially in the context of document size limitations and performance?

A : Arrays do not impact document size, allowing for unlimited data addition without performance concerns.

B : Adding elements to an array increases the risk of exceeding the BSON document size limit, potentially leading to failed updates.

C : Adding data to arrays significantly improves query performance by utilizing array-specific indexes.

D : Each addition to an array requires a complete document rewrite, which has no impact on performance or storage.

Answer: B

Question 4

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

Question 5

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

Page: 1 / 60

Total 300 Questions | Updated On: Apr 02, 2026

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