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A BigData pipeline for DotA2

Shell 0.54% Python 4.92% JavaScript 23.94% HTML 0.33% CSS 70.26%
big-data data-engineering database-modeling

dota-pipeline's Introduction

Data pipeline for DotA2

Authors

  1. Bhaargav Sriraman
  2. Prabhjot Singh Rai
  3. Suresh Siddharth
  4. Vishwesh Mishra

About

This project was implemented as a part of the Big Data Engineeting and Architechture course at Univeristy of Minnesota

This project’s objective is to design and develop a system that can take a look at the data generated by people playing the game of DotA2 and perform analytics-at-scale on it. The aim is to provide general global-level statistics on the game (descriptive analysis), insight on the latest trends followed by the players, as well as look into how the system can provide suggestions and strategy on how to play better (predictive analysis).

Tech Used

  1. Data Source : Steam API
  2. NoSQL Tech Used : FaunaDB
  3. Message Broker : Google PubSub
  4. Fetching and processing data : Python
  5. Querying DB : JavaScript

Additional Information

Refer the final documentation to get detailed information about the project.

dota-pipeline's People

Contributors

bhaargav006 avatar dependabot[bot] avatar psr-ai avatar sighithappens avatar vishwesh-mishra avatar

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