After you have accessed your data on BaseCRM, you will have to transform it based on two main factors,
- The limitations of the database where the data is loaded
- 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.
Also, you have to choose the right data types. Again, depending on the system you will send the 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.
The reports obtained from BaseCRM are similar to CSV files in structure. You also need to identify how to map a table into your database.
Data in Snowflake is organized around tables with a well-defined set of columns with each one having a specific data type.
Snowflake supports a rich set of data types. It is worth mentioning that a number of semi-structured data types are also supported. Snowflake allows loading data directly in JSON, Avro, ORC, Parquet, or XML format. Hierarchical data is treated as a first-class citizen, similar to what Google BigQuery offers.
There is also one notable common data type that Snowflake does not support. LOB or large object data type is not supported. Instead, you should use a BINARY or VARCHAR type. But these types are not that useful for data warehouse use cases.
A typical strategy for loading data from BaseCRM to Snowflake is to create a schema where you will map each API endpoint to a table.
Each key inside the BaseCRM API endpoint response should be mapped to a column of that table, and you should ensure the right conversion to a Snowflake data type.
You will need to ensure that as the data types from the BaseCRM API might change, and you adapt your database tables accordingly - automatic data typecasting isn’t available.
After you have a complete and well-defined data model or schema for Snowflake, you can move forward and start loading your data into the database.