Reverse ETL (Extract, Transform, Load) involves moving data from a data warehouse into tools like Google Sheets for analysis and collaboration. This process can be simplified by using libraries such as psycopg2, pandas, gspread, and gspread-dataframe to connect to Postgres databases and write data to Google Sheets. To set up access to Google Sheets, users need to create a GCP account, enable the Google Drive API, and generate credentials for server-to-server access. Once these pieces are in place, users can use Python scripts to read from Postgres, retrieve data, and write it to Google Sheets. However, as the data flow becomes more complex, issues such as custom code and scaling problems may arise, highlighting the need for integrations that can scale with the data volume and user needs.