How to load data from the NetSuite to Snowflake
Access your data on NetSuite
The first step in loading your NetSuite data to any kind of data warehouse solution is to access your data and start extracting it.
NetSuite’s data model comes into to three following versions:
- SuiteScript Model: Suitable if working with Script or the Workflow Tool.
- Web Service Model: Suitable when external applications need to connect to NetSuite.
- ODBC/JDBC Model: Available when SuiteAnalytics module is purchased. This allows you to connect to a read-only version of NetSuite using ODBC or JDBC drivers.
Although differences do exist among the aforementioned models, the main types of information are always present and, among others, include the following:
- Revenue Recognition
When working with the SuiteScript Model, you can extend the SuiteScript API using RESTlets.This way, you can deploy server-side scripts that interact with NetSuite data following RESTful principles. RESTlets offer ease of adoption for developers familiar with SuiteScript and support more behaviors than NetSuite’s SOAP-based web services, which are limited to those defined as SuiteTalk operations.
On the other hand, if you choose the Web Service model, you will have to work with NetSuite’s web services API, which is implemented using the SOAP protocol, adding some complexity to your development as you will have to manage SOAP and XML responses.
Also, keep in mind that as in every other API, you will have to respect the API usage limits and make sure that you handle errors correctly.
NetSuite is a cloud service that medium and large-sized companies widely use to manage all core business processes in a single system. Netsuite has expanded its capabilities far beyond all traditional enterprise resource planning (ERP) systems by offering its users the following:
- Enterprise Resource Planning (ERP): for managing processes like accounting, inventory, supply chain, and orders.
- Customer Relationship Management (CRM): for keeping track of the company’s interaction with current and potential customers.
- Professional services automation (PSA): for accurate planning and execution of projects.
- E-commerce: for managing order management, marketing, merchandising, financials and support.
- Retail: for satisfying omnichannel customers.
- Manufacturing: for delivering products and services.
Transform and prepare your NetSuite data for Snowflake
After you have accessed your data on NetSuite, you will have to transform it based on two main factors,
- The limitations of the database that is going to be used
- The type of analysis that you plan to perform
Each system has specific limitations on every type of data and data structure that it supports. If for example, you want to push data into Google BigQuery, then you can send nested data like JSON directly. Keep in mind that in the case you are working with the web services SOAP API you will get XML responses. 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.
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 that 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.
With the NetSuite web services API, you also have two main additional sources of complexity. When it comes to data types you have to keep in mind that SOAP is using XML to describe the service and data, so any data types that you have to map are coming from XML and might have automatically been transformed into the primitive data types of the language that you are using.
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 types of data are also supported. It is possible to load data directly in JSON, Avro, ORC, Parquet, or XML format with Snowflake. 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 NetSuite to Snowflake is to create a schema where you will map each API endpoint to a table.
Each key inside the NetSuite 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 data types from the NetSuite API might change, you will adapt your database tables accordingly. There’s no such thing as automatic data type casting.
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 NetSuite to Snowflake
Usually, data is loaded into Snowflake in a bulk way, using the COPY INTO command. Files containing 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 data directly into a service like Amazon S3, from where Snowflake can access data directly.
Updating your NetSuite data on Snowflake
As you will be generating more data on NetSuite, you will need to update your older data on Snowflake. This includes new records and updates to older records that or any reason have been updated on NetSuite for any reason.
You will need to periodically check NetSuite 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 NetSuite 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 data inserted into your database is a big and difficult issue.
The best way to load data from NetSuite to Snowflake
So far we just scraped the surface of what you can do with Snowflake and how to load data into it. Things can get even more complicated if you want to integrate data coming from different sources.
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