In this blog, I’ll share my practical experience using MongoDB with a games dataset. The exercise focused on storing, querying, and analyzing data, helping me understand how NoSQL databases work in real-world scenarios.
Step 1: Setting Up MongoDB
I used MongoDB Compass locally and created a database named gameDB. Compass provides an intuitive interface to interact with the database, visualize collections, and run queries easily.
Step 2: Importing the Games Dataset
I imported a sample games dataset in JSON format containing the following details:
Game ID
Title
Genre
Rating
Review
After importing, I could see all the games and their reviews neatly organized in the collection.
Step 3: Inserting Records Manually
To practice, I inserted 10 new game records manually. This helped me understand how new data can be added into an existing collection in MongoDB.
Step 4: Performing Queries
Top 5 Games by Rating
I identified the top 5 highest-rated games in the dataset. This helped me practice sorting and filtering data to get meaningful insights.
Counting Reviews with “Good”
I analyzed how many reviews contained the word “good.” This demonstrated MongoDB’s ability to search text across documents efficiently.
Fetching Reviews for a Specific Game
I retrieved all reviews for a specific game using its ID. This showcased how to filter data for targeted analysis.
Updating and Deleting Records
I updated the review of a game to reflect new feedback and also deleted a record that was no longer relevant. This demonstrated MongoDB’s data modification capabilities.
Step 5: Exporting Query Results
After performing the queries, I exported the results in JSON and CSV formats. This allows further analysis or sharing with others.
Conclusion
Working with MongoDB and a games dataset was a highly educational experience. Key takeaways include:
Understanding CRUD operations in NoSQL databases
Practicing data querying, sorting, and filtering
Learning to export and share data efficiently
MongoDB proves to be a powerful and flexible database, especially for datasets with dynamic or semi-structured data like game reviews.
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