Client Background
Client: A leading game development firm in the USA
Industry Type: Gaming Software
Products & Services: Gaming Software Development
Organization Size: 200+
The Problem
Our client sends records of millions of sports bets in real time from all over the world via an API. These bets are recorded in MySQL servers. We are tasked with processing and calculating the expected Profit and Loss (PNL) as per the bets records for each sport. Our goal is to analyze these records in real time via API and calculate PNL as per the game records history provided via API. This requires building a serverless application in Python (or similar) that reads all bets records and updates PNL in real time (within milliseconds, records need to be updated). The application should be capable of handling 10,000+ records of bets per second for numbers of different games, with PNL needing to be updated for each game separately.
Our Solution
To address this problem, we propose developing a Python-based serverless application that leverages machine learning models for real-time PNL calculation. The application will use the MySQL database to store and retrieve betting records. It will employ parallel computing techniques to ensure efficient processing of high volumes of data. The application will also utilize APIs to fetch real-time data and update PNL accordingly.
The application will follow these steps:
- Connect to the MySQL database to access the betting records.
- Use an API to fetch real-time betting data.
- Process the data using Python scripts.
- Apply machine learning models to predict the outcome of each bet.
- Calculate the PNL for each bet according to the predicted outcome.
- Update the PNL in the MySQL database in real time.
Solution Architecture
Deliverables
- A Python-based serverless application for real-time PNL calculation.
- An interface for visualizing the calculated PNL in real time.
- Documentation detailing how to use and maintain the application.
Tech Stack
- Tools used
- Python: For writing the serverless application.
- MySQL: For storing and retrieving betting records.
- Machine Learning Models: For predicting the outcome of bets.
- Language/techniques used
- Python
- Models used
- OOPS
- Skills used
- Database Analysis & API Development: To design and optimize the MySQL database.
- Python Programming: To write the serverless application.
- OOPS: To make the game functioning algorithms.
- Databases used
- SQL
What are the technical Challenges Faced during Project Execution
- One of the main challenges we faced was handling the high volume of data coming in real time. To overcome this, we employed parallel computing techniques to efficiently process the data. Another challenge was updating the PNL in the MySQL database in real time. We solved this by designing the application to update the PNL immediately after it is calculated.
How the Technical Challenges were Solved
- We addressed the high volume of data challenge by using parallel computing techniques. This allowed us to process a large number of records simultaneously, ensuring efficient data handling.
- To solve the real-time PNL update issue, we designed the application to update the PNL immediately after it is calculated. This ensured that the PNL was always up-to-date, meeting the requirement of real-time PNL calculation.
Business Impact
The implementation of the proposed Python-based serverless application for real-time PNL calculation had significant positive impacts on our business operations.
Firstly, the application enabled us to process and analyze millions of sports bets in real time, enhancing our decision-making capabilities and allowing for quicker responses to changes in the betting market. This improved our ability to predict outcomes and adjust our betting strategies accordingly.
Secondly, the application significantly reduced the time taken to calculate PNL, from hours to mere minutes. This resulted in faster decision-making processes and timely financial reporting, which were crucial for our clients and investors.
Lastly, the application’s ability to handle high volumes of data and provide real-time updates facilitated a more globalized betting market. With real-time data and digital platforms, geographical boundaries became less relevant, allowing bettors from around the world to place bets on any event globally, with real-time odds reflecting local nuances and dynamics. This led to increased liquidity and more competitive odds.
Overall, the successful implementation of the application led to a more efficient, accurate, and timely PNL calculation process, resulting in improved business performance and customer satisfaction.
Project Snapshots
Project website url
Summarize
Summarized: https://blackcoffer.com/
This project was done by the Blackcoffer Team, a Global IT Consulting firm.
Contact Details
This solution was designed and developed by Blackcoffer Team
Here are my contact details:
Firm Name: Blackcoffer Pvt. Ltd.
Firm Website: www.blackcoffer.com
Firm Address: 4/2, E-Extension, Shaym Vihar Phase 1, New Delhi 110043
Email: ajay@blackcoffer.com
Skype: asbidyarthy
WhatsApp: +91 9717367468
Telegram: @asbidyarthy
