https://github.com/kaushik-puttaswamy/dynamic-movie-booking-insights-platform-using-snowflake
The Dynamic Movie Booking Insights Platform processes real-time booking data using Snowflake’s Dynamic Tables, Streams, and Tasks to deliver actionable insights. It features an interactive Streamlit dashboard for visualizing revenue, sales trends, and booking metric.
https://github.com/kaushik-puttaswamy/dynamic-movie-booking-insights-platform-using-snowflake
businessintelligence changedatacapture dataprocessing datavisualization dynamictables moviebooking python realtimeanalytics revenueinsights snowflake sql streamlit
Last synced: 3 months ago
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The Dynamic Movie Booking Insights Platform processes real-time booking data using Snowflake’s Dynamic Tables, Streams, and Tasks to deliver actionable insights. It features an interactive Streamlit dashboard for visualizing revenue, sales trends, and booking metric.
- Host: GitHub
- URL: https://github.com/kaushik-puttaswamy/dynamic-movie-booking-insights-platform-using-snowflake
- Owner: Kaushik-Puttaswamy
- Created: 2025-01-10T23:12:26.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-15T23:33:36.000Z (5 months ago)
- Last Synced: 2025-01-16T00:21:57.531Z (5 months ago)
- Topics: businessintelligence, changedatacapture, dataprocessing, datavisualization, dynamictables, moviebooking, python, realtimeanalytics, revenueinsights, snowflake, sql, streamlit
- Language: Python
- Homepage: https://www.datascienceportfol.io/kaushikputtaswamy/projects/10
- Size: 938 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Dynamic Movie Booking Insights Platform Using Snowflake
## Overview
The Dynamic Movie Booking Insights Platform is a robust solution designed to process real-time movie ticket booking data and provide actionable insights. By leveraging Snowflake’s Dynamic Tables, Streams, Tasks, and integrated Streamlit, the platform delivers a seamless analytics experience. The interactive dashboard allows businesses to track revenue, ticket sales, and booking trends with ease.
## Features
1) Real-Time Data Processing:
• Tracks changes in booking data using Snowflake Streams and Tasks.
• Handles CDC (Change Data Capture) events like INSERT, UPDATE, and DELETE.
2) Dynamic Insights:
• Aggregates data in real-time using Snowflake’s Dynamic Tables.
• Provides metrics such as revenue, tickets sold, cancellations, and more.
3) Integrated Streamlit Dashboard:
• Hosted directly in Snowflake for a zero-setup experience.
• Offers filters for date range and booking status.
• Visualizes data through tables, metrics, and charts.
## Technology Stack
### Snowflake
• Streams: For capturing changes in booking data.
• Tasks: To automate processing and aggregation of data.
• Dynamic Tables: To enable real-time analytics.
• Python Worksheets: For developing and running Python-based logic.
### Streamlit (Built into Snowflake)
• For creating the interactive and responsive dashboard.
## Setup Guide
### Step 1: Set Up Database in Snowflake
1. Log in to your Snowflake account.
2. Create a new worksheet.
3. Copy the content of the snowflake_dynamic_tables.sql file into the worksheet and execute it.
• This script creates:
• The database movies and required tables.
• Streams and tasks for processing CDC events.
• Dynamic tables for analytics.
4. Activate the tasks:
``` ALTER TASK ingest_cdc_events_task RESUME; ```
``` ALTER TASK refresh_movie_booking_insights RESUME; ```
### Step 2: Launch the Streamlit Dashboard
1. Open a Python Worksheet in Snowflake.
2. Copy the contents of the streamlit_app.py file into the worksheet.
3. Click the Run button in the worksheet to ensure no errors occur.
4. Click the Streamlit button (usually located in the top-right corner of the worksheet) to launch the interactive dashboard.
## Using the Dashboard
### Filters
• Date Range: Filter booking data by selecting a specific date range.
• Booking Status: Filter bookings by status (BOOKED, CANCELLED, COMPLETED, or all).
### Insights
#### Metrics:
• Total Bookings
• Total Tickets Sold
• Total Revenue
#### Charts:
• Revenue by Booking Status
• Tickets Sold by Status
• Bookings and Revenue by Movie
#### Tables:
• Detailed revenue and booking data by movie or status.
## Dashboard Preview
Below is a preview of the interactive dashboard hosted in Snowflake Streamlit:
Link to Dashboard: https://app.snowflake.com/europe-west3.gcp/qv46679/#/streamlit-apps/MOVIES.PUBLIC.R2OC4N65TX1QZZ7F?ref=snowsight_shared
## Folder Structure
dynamic-movie-booking-platform/
│
├── snowflake_dynamic_tables.sql # Snowflake SQL script for database setup
├── streamlit_app.py # Streamlit app for the interactive dashboard
├── README.md # Project documentation
└── requirements.txt # Python dependencies
## How It Works
1. Data Ingestion.
• Booking data is inserted, updated, or deleted in the raw_movie_bookings table.
• The movie_bookings_stream captures CDC events (insert, update, delete).
2. Data Processing:
• The task ingest_cdc_events_task processes CDC events and stores them in movie_booking_cdc_events.
• Dynamic tables (movie_bookings_filtered and movie_booking_insights) aggregate and filter the data for analysis.
3. Visualization:
• The Streamlit app fetches data directly from Snowflake tables and visualizes it dynamically.
## Key SQL and Python Components
1. Snowflake SQL Components:
• Streams: movie_bookings_stream to track CDC changes.
• Tasks: ingest_cdc_events_task and refresh_movie_booking_insights for data processing and refreshing.
• Dynamic Tables:
• movie_bookings_filtered: Filters relevant booking data.
• movie_booking_insights: Aggregates key metrics and insights.
3. Streamlit Dashboard:
• Filters data based on user input (date range and status).
• Displays metrics, charts, and tables for easy analysis.
## Future Enhancements
#### Predictive Analytics:
• Use machine learning models for demand forecasting and revenue prediction.
#### User Management:
• Add authentication and role-based access control.
#### Custom Notifications:
• Notify users about booking trends or anomalies.
#### Data Export:
• Provide an option to export data as CSV or Excel.
🚀 Experience seamless movie booking analytics directly within Snowflake!