Suppose your team just requested a NetSuite to Snowflake connection on priority. We know you don’t want to keep your data scientists and business analysts waiting to get critical business insights. As the most direct approach, you can go straight for the CSV files exporting if this is a one-time thing.

Or, hunt for a no-code tool that fully automates & manages data integration for you while you focus on your core objectives. Well, look no further. This article provides a step-by-step guide to connecting NetSuite to Snowflake effectively and quickly delivering data to your finance team. 

What is NetSuite?

NetSuite is a widely adopted cloud service by medium and large-sized enterprises, serving as a comprehensive system to streamline all essential business processes. It has surpassed the capabilities of traditional Enterprise Resource Planning (ERP) systems by providing users with the following functionalities:

  • Enterprise Resource Planning (ERP):
    • Efficient management of accounting, inventory, supply chain, and order processing processes.
  • Customer Relationship Management (CRM):
    • Tracking the company’s interactions with both current and potential customers.
  • Professional Services Automation (PSA):
    • Accurate planning and execution of projects for enhanced project management.
  • E-commerce:
    • Comprehensive management of order processing, marketing, merchandising, financials, and customer support.
  • Retail:
    • Satisfying omnichannel customers through robust retail management capabilities.
  • Manufacturing:
    • Facilitating the delivery of products and services through effective manufacturing processes.

NetSuite’s cloud-based solution goes beyond the conventional ERP system, offering an integrated platform that empowers businesses to handle diverse aspects of their operations efficiently.

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Introduction to Snowflake

Snowflake is a relational Cloud Data Warehouse that can also support semi-structured data formats, including ORC, JSON etc. You can ingest data into Snowflake from many sources including Amazon S3, GCS, etc. The capabilities of Snowflake in processing, and storing data makes it a popular solution.

Next, let’s get into the methods for moving data from Netsuite to Snowflake.

Automate the Data Replication Process Using a No-Code Platform

Hevo is the only real-time ELT No-code data pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. With integration with 150+ Data Sources (40+ free sources), we help you not only export data from sources & load data to the destinations but also transform & enrich your data, & make it analysis-ready with zero data loss.

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Here’s how Hevo, a cloud-based ETL tool, makes NetSuite to Snowflake data replication ridiculously easy:

Step 1: Configure NetSuite as a Source

Learn more about how to Authenticate and Configure your NetSuite Source here.

Step 2: Configure Snowflake as a Destination

Learn more about how to configure Snowflake as the destination here.

Step 3: All Done to Setup Your ETL Pipeline

Once your NetSuite to Snowflake ETL Pipeline is configured, Hevo will collect new and updated data from NetSuite every five minutes (the default pipeline frequency) and duplicate it into Snowflake. Depending on your needs, you can adjust the pipeline frequency from 5 minutes to an hour.

Data Replication Frequency

Default Pipeline FrequencyMinimum Pipeline FrequencyMaximum Pipeline FrequencyCustom Frequency Range (Hrs)
1 Hr15 Mins24 Hrs1-24

In a matter of minutes, you can complete this No-code & automated approach of connecting NetSuite to Snowflake using Hevo and start analyzing your data.

Hevo classifies the NetSuite objects into three categories to distinguish the type of data being replicated:

  • Transaction: Transaction objects have data about your business, such as financial agreements and inventory adjustments. All the objects listed under Transaction are replicated in the Transaction table at the destination.
  • Item: Item objects have data of inventory items that you buy and sell, assemblies you manufacture, or services you provide to customers. All the objects listed under Item are replicated in the Item table.
  • Standard: All other objects are classified as standard objects and replicated in their respective tables.

With these simple steps, you can complete the NetSuite to Snowflake data integration process in just a few minutes.

Some features of Hevo are,

  • Data Transformation: Hevo provides a simple interface to cleanse, modify, and transform your data through drag-and-drop features and Python scripts. It can accommodate multiple use cases with its pre-load and post-load transformation capabilities.
  • Schema Management: With Hevo’s auto schema mapping feature, all your mappings will be automatically detected and managed to the destination schema.
  • Scalable Infrastructure: With the increase in the number of sources and volume of data, Hevo can automatically scale horizontally, handling millions of records per minute with minimal latency.

Replicate Data from NetSuite to Snowflake Using CSV

Some prerequisites to manually migrate data from NetSuite to Snowflake are access to NetSuite and Snowsight.

Step 1: Exporting Data from NetSuite to CSV

  • Log in to the NetSuite interface
  • Navigate to the top right corner of the home page and click on the Setup button.
  • Click on Import/Export > Export Tasks > Full CSV Export from the drop-down menu.
  • Click on the Submit button.
  • On the popup, select Save this file to disk and OK
  • Assign a unique name to the file in the Save As window.
  • Download the file as a zip, and you can extract it to access the CSV file containing the NetSuite data.

Step 2: Importing NetSuite Data into Snowflake

  • Log in to your Snowflake account
  • On the main dashboard, in the top left corner, select the Data> Databases option to view your databases.
  • Select the database to load NetSuite data from step 1
  • If no database exists, click on the +Database button in the top right corner.
  • Click on the newly created database and create a new schema – Click Create>Table>Standard
  • On the SQL interface, Write a SQL query to generate a table that aligns with the structure of the CSV file downloaded from step1
  • Select the database table and click on the Load Data button in the top-right corner.
  • Specify the file format as CSV and fill in other optional fields
  • Now, the CSV file will be loaded into your Snowflake database, and you can preview the data to verify the requirements.

These steps help you seamlessly migrate data from NetSuite to Snowflake.

You can get more insight into loading CSV files through the web interface, along with other handy methods here.

This 2-step process using CSV  is a great way to replicate data from NetSuite to Snowflake effectively. It is optimal for the following scenarios:

  • One-Time Data Replication: When your finance team needs the NetSuite data only once in a long period of time. 
  • No Data Transformation Required: If there is a negligible need for data transformation and your data is standardized, then this method is ideal. 
  • Small Amount of Data: Since the amount of data is small, the accuracy of data replication would be high, making this method a good fit.

In the following scenarios, using CSV might not be a great fit:

  • Data Mapping: Only basic data can be moved. Complex configurations cannot take place. There is no distinction between text, numeric values, and null and quoted values.
  • Time Consuming:  If you plan to export your data frequently, there may be better choices than the CSV method since it takes time to replicate the data using CSV files. 

Limitations of Using Manual Method

  • Exporting data, formatting it, and importing it to another database require time and effort from the data engineering team.
  • As it’s not leveraging the scope of automation, errors that arise due to manual intervention will be more. 
  • Your data can consist of complex structures that wouldn’t be well written in CSV format.
  • When you have to transform the raw data every single time. With the increase in data sources, you would have to spend a significant portion of your engineering bandwidth creating new data connectors.

Using COPY INTO Command for replicating

You can use COPY INTO command to load data into Snowflake. The data in JSON format will be either in your local file system or in S3. You can invoke a COPY INTO command on the Snowflake instance which will copy the data to the warehouse. You can also use PUT command to keep the data in staging before evoking COPY command.

Next, let’s understand some steps for accessing data on Snowflake.

Steps to access your data on NetSuite

The table below explains NetSuite’s data model comes into three versions:

Versions of data modelUse cases
SuiteScript Model When working with Script or the Workflow Tool
Web Service ModelWhen you want to connect external applications to NetSuite
ODBC/JDBC ModelWhen you purchase SuiteAnalytics module

A few things when you work with these versions

  • You can extend the SuiteScript API using RESTlets in SuiteScript Model. This will help you deploy server-side scripts that interact with NetSuite data adhering to RESTful principles. RESTlets provide easy use for people who know SuiteScript. It also supports more behaviors than NetSuite’s SOAP-based web services that are constrained to SuiteTalk operations.
  • You will be working with NetSuite’s web services API under Web Service model. This can be deployed using the SOAP protocol, which adds difficulty to your development as you will have to manage SOAP and XML responses.

Modify and prepare data for Snowflake

  • Once you access data on NetSuite, consider the limitations of your database and analysis you want to perform on that data to decide the type of transformation.
  • When you use web services SOAP API, you get XML responses. When the data is tabular, you should flatten the data like you do for JSON.
  • Choose the right data type, as it’s important to understand the expressivity of the queries and restrict the analysis.

While using NetSuite web services API,

  • SOAP is utilizing XML to describe the service and your data. So, the data types you map are from XML and will be, by default, transformed into the primitive data types of the language that you use.

What Can You Achieve by Migrating Your Data from NetSuite to Snowflake?

Here’s a little something for the data analyst of your team. We’ve mentioned a few core insights you could get by replicating data from NetSuite to Snowflake.

What can you achieve by moving data from Netsuite to Snowflake?

  • You can leverage many additional features like historical analysis, data cloning, scalable storage, and computing in Snowflake for storing your data. 
  • NetSuite’s capabilities are only for small to intermediate datasets, which is not enough for carrying out data analysis on a large scale. A data warehouse can help here.
  • Various iIntegrations with tools and ecosystem of Snowflake is unparallel and you can get benefitted out of it.

Summing Up

CSV files is the right path for you when your team needs to perform NetSuite Snowflake integration once in a while. However, an ETL solution becomes necessary if there are rapid changes in the source and frequent data replication needs to be done to meet the data demands of your product or finance channel. You can free your engineering bandwidth from these repetitive & resource-intensive tasks by selecting Hevo’s 150+ plug-and-play integrations.

Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs. No need to go to your data warehouse for post-load transformations. You can run complex SQL transformations from the comfort of Hevo’s interface and get your data in the final analysis-ready form. 

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Share your experience of replicating data from NetSuite to Snowflake! Let us know in the comments section below!

Harsh Varshney
Research Analyst, Hevo Data

Harsh comes with experience in performing research analysis who has a passion for data, software architecture, and writing technical content. He has written more than 100 articles on data integration and infrastructure.

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