Dumpster diving for data: The MongoDB experience` discusses the challenges of extracting data from MongoDB and making it available in a SQL store. The article highlights the difficulties around ingesting data into a SQL database due to MongoDB's flexible schema, document-based storage, and potential data inconsistencies. It explores the requirements that drive this process, including business user access, ecosystem of integrations and tools, standardization for consistency, and data transformation & modelling capabilities. The article also delves into the differences between BSON and JSON, and how MongoDB can be solved by converting BSON to JSON. Additionally, it discusses the importance of data typing, cleaning, and unpacking nested JSON into tables or keeping it as JSON. Finally, it introduces a tool called `dlt` that helps load Mongo data into SQL databases, making the process more efficient and robust.