Episode 1: The Data Adventure Begins
Dive into the vast world of Yelp reviews, where every customer’s opinion shapes the experience of millions. Our stage? MongoDB — the NoSQL powerhouse perfect for handling this diverse data. Our mission? Insert, query, update, and explore insights hidden in these reviews.
Act 1: Setting the Scene — MongoDB Setup
Like any great data story, we start by setting up MongoDB. Whether on local machines or the cloud with MongoDB Atlas, we created a database named yelpDB and a collection reviews — the heart of our review operations.
Act 2: Rolling Out the Cast — Insert Records
With our stage ready, it was time to introduce the actors. We manually inserted 10 sample Yelp reviews, each carrying vital attributes like business_id, review_id, text of the review, and rating.
Act 3: The Rating Royalty — Top 5 Businesses
Who reigns supreme in the Yelp kingdom? MongoDB’s aggregation framework helped us uncover the top 5 businesses with the highest average ratings, proving once again that stars have power.
Act 4: The Good Word Mystery
What’s the hype about the word “good”? We counted how many reviews mentioned “good” to catch the pulse of positivity (or criticism) in the community.
Act 5: Reviews Spotlight — A Business Tale
Because every business has its story, we drilled down to look at all reviews for a particular business_id — say "b2" — gathering the voices behind the numbers.
Act 6: The Plot Twists — Update & Delete
No story remains static. We performed an update to a review’s rating (e.g., changing rating of review "r1") and deleted another review ("r4") that no longer fit the narrative.
Exporting the Chronicles
Every great story deserves to be shared. We exported our curated review dataset and query results into JSON and CSV formats for further analysis, archival, and storytelling across platforms.
By the end of our Yelp Reviews MongoDB journey, we had:
✅ Inserted sample review records
✅ Aggregated businesses by average rating
✅ Counted review text occurrences
✅ Queried reviews by business_id
✅ Updated and deleted records
✅ Exported data for external use
💡 This hands-on journey mirrors real-world data engineering workflows — from ETL to insights, data maintenance, and exporting essential data products.
Stay tuned for more seasons of MongoDB exploration and data adventures!
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