How to load data from the Chargebee to Snowflake
Access your data on Chargebee
The first step in loading your Chargebee data to any kind of data warehouse solution is to access your data and start extracting it.
Chargebee has a well-designed API that can be used to access the platform programmatically. It is built around more than 20 different resources, something that indicates the richness of the platform and the API. These resources include things like Customers and Events. So, in the data, you will find from typical pages that do not change that often like customers, to time series data like events. You need to account for the different types of data that are included and design your database schema accordingly.
Chargebee as any other REST API can be accessed over the web with HTTP requests. They also offer and maintain a large number of different SDKs for some of the most popular languages and frameworks.
In addition to the above, the things that you have to keep in mind when dealing with any API like the one Chargebee has, are:
- Rate limits. Every API has some rate limits that you have to respect.
- Authentication. You authenticate on Chargebee using an API key.
- Paging and dealing with a big amount of data. Platforms like Chargebee tend to generate a lot of data, as financial transactions and subscription management involve many different events that can happen. Pulling big volumes of data out of an API might be difficult, especially when you consider and respect any rate limits that the API has.
Transform and prepare your Chargebee data for Snowflake
After you have accessed your data on Chargebee, you will have to transform it based on two main factors,
- The limitations of the database that the data will be loaded onto
- 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 for example, you want to push data into Snowflake then you can send nested data like JSON directly. But when you are dealing with tabular data stores, like PostgreSQL, this is not an option. Instead, you will have to flatten out your data before loading it into the database.
Also, you have to choose the right data types. Again, depending on the system that 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.
Chargebee has a very rich data model, where many of the resources that you can access might have to flatten out and be pushed in more than one table. Also, there is a wealth of time series data that is useful in understanding the behavior of your customer.
For the above reasons, you should model your database carefully before moving forward with the loading of data from Chargebee into it.
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. With Snowflake, is possible to load directly data 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 is not supported by Snowflake. LOB or large object data type is not supported, instead, you should use a BINARY or VARCHAR type instead. But these types are not that useful for data warehouse use cases.
A typical strategy for loading data from Chargebee to Snowflake is to create a schema where you will map each API endpoint to a table.
Each key inside the Chargebee API endpoint response should be mapped to a column of that table and you should ensure the right conversion to a Snowflake data type.
Of course, you will need to ensure that as the data types from the Chargebee API might change, you will adapt your database tables accordingly, there’s no such thing as automatic data typecasting.
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.
Load data from Chargebee to Snowflake
Usually, data is loaded into Snowflake in a bulk way, using the COPY INTO command. Files containing the data, usually in JSON format, are stored in a local file system or in Amazon S3 buckets. Then a COPY INTO command is invoked on the Snowflake instance and data is copied into the data warehouse.
The files can be pushed into Snowflake using the PUT command, into a staging environment before the COPY command is invoked.
Another alternative is to upload the data directly into a service like Amazon S3 from where Snowflake can access the data directly.
Updating your Chargebee data on Snowflake
As you will be generating more data on Chargebee, you will need to update your older data on Snowflake. This includes new records together with updates to older records that for any reason have been updated on Chargebee.
You will need to periodically check Chargebee for new data and repeat the process that has been described previously while updating your currently available data if needed. Updating an already existing row on a Snowflake table is achieved by creating UPDATE statements.
Another issue that you need to take care of is the identification and removal of any duplicate records on your database. Either because Chargebee does not have a mechanism to identify new and updated records or because of errors on your data pipelines, duplicate records might be introduced to your database.
In general, ensuring the quality of the data that is inserted into your database is a big and difficult issue.
The best way to load data from Chargebee to Snowflake
So far we just scraped the surface of what can be done with Snowflake and how to load data into it. The way to proceed relies heavily on the data you want to load, from which service they are coming from, and the requirements of your use case.
Things can get even more complicated if you want to integrate data coming from different sources. A possible alternative, instead of writing, hosting, and maintaining a flexible data infrastructure, is to use a product like RudderStack that can handle this kind of problem automatically for you.
RudderStack integrates with multiple sources or services like databases, CRM, email campaigns, analytics, and more. Quickly and safely move all your data from Chargebee to Snowflake and start generating insights from your data.