After you have accessed data on Freshdesk, you will have to transform it based on two main factors,
1. The limitations of the database that is going to be used
2. The type of analysis that you plan to perform
Each system has specific limitations on the data types and data structures that it supports. If you want to push data into Google BigQuery, you can send nested data like JSON directly.
Of course, when you are dealing with tabular data stores, like Microsoft SQL Server, this is not an option. Instead, you will have to flatten out your data, just as in the case of JSON, before loading it into the database.
Also, you have to choose the right data types. Again, depending on the system, you will send data to and the data types that the API exposes to you, you will have to make the right choices. These choices are important because they can limit the expressivity of your queries and limit your analysts on what they can do directly out of the database. Freshdesk has a very limited set of available data types, which means that your work to do these mappings is much easier and straightforward but equally important with any other data source case.
Due to the rich and complex data model that Freshdesk follows, some of the provided resources might have to be flattened out and be pushed in more than one table.