BigQuery and Postgres have great tools for loading Big Data efficiently when data is immutable, distributed across tables with timestamp columns. To prepare for this, indexes must be created in the Postgres database before loading processes into BigQuery. The use of wild card tables pattern allows for efficient storage on both sides. A script can be used to automate the uploading process by using the BigQuery CLI and a bash script that compresses data before uploading it. This enables real-time data loading with just a single day's data, making it suitable for large-scale projects. The script can be scheduled to run daily or hourly, allowing for nearly real-time data updates.