Dockerized Data Pipeline that analyzes the sentiment of tweets

The goal of this project is to develop a dockerized data pipeline with following steps:

• Collecting tweets with a Python script
• Storing tweets in a MongoDB database
• ETL Job: Extracting the tweets from MongoDB, performing a sentiment analysis of the tweets and stroing the results in a second database (Postgres)
• 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