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Dealing with 1:N nested data when transforming

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I'm trying to leverage the advantages of DocumentDB / Elastic / NoSQL for retrieving big data and to visualize it. I want to use PowerBI to do that, which is pretty good, however, I have no clue how to model a document which has a 1:N nested data field. E.g.

{
name: string,
age: int
children: [ { name: string }... ]
}


In a normal case, you would flatten the table by expanding the nested values and joining them, but how does one do that when it's 1:N / A list. Is there a way to maybe extract that into it's own table?

I've been thinking about making a bridge which translates a document into data tables, but that feels like an incorrect way to go, and further proves some complications with regards to how many endpoints and queries there should be made.

I can't help but think this is a solved issue, as many places analyse and visualize large amounts of data stored in no sql. The alternative is a normalized relational database, but having millions and millions of entries in that which you analyze also seems incorrect when nosql is tuned for these scenarios.

 

How is this dealt with?


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