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: Jan 28, 2026

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Question 1

A MongoDB data modeler is optimizing the performance of an application that frequently executes the following query:

db.orders.find(

{ status: "shipped", deliveryDate: { $lte: new Date("2023-12-31") } }

).sort({ deliveryDate: -1 })

The explain method reveals the following key details indicating the query is not efficiently utilizing indexes:

{

"queryPlanner": {

...

"winningPlan": {

"stage": "SORT",

"sortPattern": { "deliveryDate": -1 },

...

"inputStage": {

"stage": "FETCH",

"inputStage": {

"stage": "IXSCAN",

"keyPattern": { "status": 1 },

...

}

"executionStats": {

"executionSuccess": true,

"nReturned": 100,

"executionTimeMillis": 120,

"totalKeysExamined": 500,

"totalDocsExamined": 500,

...

}

What action should the data modeler take to enhance the performance of this query?

A : Create a compound index on status and deliveryDate in descending order to match the sort pattern.

B : Create an index on the deliveryDate field to optimize the sort operation.

C : Create a compound index on status and deliveryDate in ascending order.

D : Remove the sort operation to decrease the complexity of the query.

Answer: A

Question 2

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 3

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 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 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: Jan 28, 2026

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