Dockerized Data Pipeline that analyzes the sentiment of tweets

This project was created during the @spicedacademy boot camp. The goal of this project is to develop a dockerized data pipeline with following steps:

① Collecting tweets with a Python script

② Storing tweets in a MongoDB database

③ ETL Job: Extracting the tweets from MongoDB, performing a sentiment analysis of the tweets and stroing the results in a Postgres database

④ Loading the tweets and the tweets sentiment in a Postgres database

The pipeline should look like this in the Docker Desktop:

This is what the Postgres DB with the tweets and corresponding sentiment score could look like:

To do:

• Finish the Slack bot and add it to the project description