Using the Google Sheets `dlt` pipeline in analytics and ML workflows

Google Sheets has limitations for storage and processing of large-scale complex data, but its ease of setup and intuitive workflow make it suitable for tracking and analyzing smaller datasets. To overcome these limitations, an ETL pipeline is needed to combine the Google Sheets data with organizational data in a data warehouse. The `dlt` pipeline makes it easy to set up and deploy a Google Sheets -> data warehouse pipeline. This can be used for various use-cases such as measuring marketing campaign ROI by connecting reporting tools to the combined data, or evaluating the performance of machine learning products by combining annotated training data with product usage data in a data warehouse.

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