Extracting Data from NetSuite2.com: Your Go To Guide

If you’re integrating or considering further leveraging your NetSuite data, there are valuable opportunities you may not have explored yet.

First things first – if you are already extracting NetSuite data using NetSuite.com you need to take action now. NetSuite.com will be discontinued in early 2026, requiring organizations to migrate to NetSuite2.com to maintain access to their data and support. The migration involves significant changes in data structure, security protocols, and query languages, necessitating careful planning and execution.

This guide outlines the steps to take to integrate NetSuite2.com data, how to migrate smoothly if you’re still on NetSuite.com, and ways to optimize data integration and analytics on NetSuite 2.0.

Check out our Migrating to NetSuite2.com webinar, where Rivery’s Head of Product Marketing, Ariel Pohoryles, and Nick Nowlan, AMER Solutions Engineering Lead at Rivery, discuss how to successfully migrate and maximize the value of your NetSuite data. Check out that webinar recording here.

The Business Value of Pulling Data from NetSuite

The common business value of extracting data from NetSuite lies in its operational impact. Syncing NetSuite data with other applications creates a unified ecosystem that optimizes business processes, increases efficiency, and enables automation. As the core of many businesses, NetSuite integrates seamlessly with various applications to drive these efficiencies.

For example, platforms like Boomi offer predefined integration templates to accelerate common NetSuite use cases, such as:

• Lead-to-Cash Process: Integrating Salesforce leads with NetSuite opportunities to streamline sales workflows.
• E-commerce Optimization: Connecting NetSuite with Shopify to enhance customer experiences.
• Professional Services Management: Syncing NetSuite OpenAir with Salesforce to improve project delivery processes.

These integrations often occur in near real-time, ensuring data flows to the right systems where users need it.

Additional Operational Use Cases

Beyond application syncing, there are operational challenges that NetSuite alone may not fully address, such as:

• Month-End Closures: Advanced financial reporting and scenario planning beyond NetSuite’s standard capabilities.
• Billing System Reconciliation: Companies with external billing platforms (e.g., SaaS businesses with consumption-based models) often need custom reconciliation processes.
• Historical Snapshots: Capturing and freezing data at specific points for comparisons and scenario analysis.
• Budget vs. Actuals Comparisons: Enhancing financial planning with external datasets.
• Monitoring & Process Automation: Managing workflows beyond NetSuite’s native capabilities, often involving manual spreadsheets or third-party applications.

Why Extract NetSuite Data to a Data Warehouse

To address these challenges, organizations integrate NetSuite data into a modern data platform—typically a centralized data warehouse like Snowflake or a lakehouse such as Databricks. This approach enables businesses to:

• Combine NetSuite data with data from other sources like Salesforce and Shopify.
• Perform advanced calculations and reconciliations in a scalable environment.
• Deliver insights back to operational tools, including NetSuite itself.
• Enable analytics via BI tools like Tableau, Power BI, and Sigma.
• Push data into business communication channels like Slack or AI-driven platforms such as Amazon Q.

Rivery plays a crucial role in moving NetSuite data to a data warehouse or lakehouse, facilitating seamless integration and automation.

Steps for Migration from NetSuite.com to NetSuite2.com

1. Understand the Change
   Review the official NetSuite documentation to educate yourself on the migration process and understand the impact on your data structure and workflows.
2. Content Audit
   Assess your existing NetSuite data and determine what needs to be migrated. Identify key reports and assets, and remove outdated or redundant data to streamline the transition.
3. Map Analysis
   Use NetSuite’s official mapping documentation and community resources to analyze structural differences between NetSuite.com and NetSuite2.com. Identify changes in tables, field names, and data types to adjust your transformation logic accordingly.
4. Define Your Approach
   Update your data transformation processes to align with the new NetSuite2.com model instead of forcing data into the older format. Where necessary, use views to bridge gaps and optimize migration.
5. Check and Double-Check
   Migrate in phases and conduct thorough testing at every level, including the data warehouse and reporting layers, to ensure accuracy and consistency across platforms.

How to easily extract NetSuite2.com data with Rivery

This guide walks through the step-by-step process of setting up a Source to Target River in Rivery to replicate NetSuite data into Snowflake efficiently. If you prefer a video walkthrough, you can follow along the below video.

Step 1: Creating a Source to Target River

To begin, log in to Rivery and navigate to the Source to Target River section. Since NetSuite is a prebuilt native source in Rivery, we will use this type of river for our data pipeline.

1. Click Create Source to Target River.
2. Search for and select NetSuite Analytics as the data source. Note: that NetSuite Analytics refers to NetSuite.com2.

Step 2: Authenticating the NetSuite Connection

Before pulling data, Rivery requires authentication to NetSuite:

1. Click New Connection and enter your NetSuite credentials.
2. Review and grant the necessary permissions and roles for Rivery to access and replicate data.
3. Select the specific objects you want to grant access to for schema exploration in Rivery.

Step 3: Choosing the River Mode

Rivery provides different modes for data extraction:

• Multi-Table Mode: Grants access to all objects and columns the NetSuite user has permission to see. Users can later select specific tables and columns to replicate in the schema tab.
• Custom Query Mode: Enables the use of SuiteQL within Rivery to define data extraction more precisely.

For this guide, we will proceed with Multi-Table Mode.

Step 4: Selecting the Target Destination (Snowflake)

Once the data source is set up, we must configure the destination:

1. Choose your data target (i.e. Snowflake).
2. Enter the necessary credentials for your target access.

Step 5: Configuring Data Loading Settings

Rivery requires a pre-configured database and schema in Snowflake. Once this is set up:

• Rivery will automatically create the necessary tables and columns.
• Schema changes (such as column additions, deletions, or data type modifications) are handled dynamically.
• Choose a data loading method:
  • Upsert-Merge: Keeps data in sync with live updates.
  • Append-Only: Adds new rows without modifying existing data.
  • Overwrite: Replaces existing data entirely.

Step 6: Configuring the Schema

Navigate to the Schema Tab in Rivery to refine the data pipeline:

1. Select one or many  tables to replicate (e.g., Transaction Accounting Line).
2. If needed to change the defaults, select individual columns to include, define Primary Keys, or set up data type conversions.
3. Add Calculated Columns, which Rivery creates dynamically during data loads.

Step 7: Setting the Extraction Method

Define how Rivery extracts data from NetSuite:

• Extract All: Pulls the entire dataset each time.
• Incremental Extraction (recommended): Extracts only the modified records based on a timestamp or running number, ensuring efficiency and performance.

Step 8: Scheduling Data Syncs

Rivery allows granular scheduling options:

• Set sync frequency (e.g., every 5 minutes, hourly, daily, etc.).
• Use cron expressions for custom scheduling.

Step 9: Leveraging Rivery’s NetSuite to Snowflake Kit

To streamline analytics, Rivery offers prebuilt Kits, which are ready-made templates for transforming and aggregating data.

1. Install the NetSuite to Snowflake Kit in Rivery.
2. Assign the previously created NetSuite source and Snowflake target.
3. Let the Kit automate transformations, converting raw NetSuite tables into optimized fact and dimension tables.

Step 10: Reviewing Data in Snowflake

Once the pipeline is active:

• Navigate to Snowflake and verify that all tables have been created.
• Confirm that transformations have executed correctly.
• Schedule the pipeline to refresh data at your preferred intervals.

Moving Forward with NetSuite2.com Data

NetSuite holds a wealth of valuable business data, but its true power comes from integrating that data with the rest of your tech stack. By centralizing NetSuite data in a data warehouse or BI tool, organizations can move beyond standard reports and unlock advanced analytics, real-time visibility, and cross-platform insights. Custom dashboards built on unified data enable teams to track performance with precision, optimize financial processes, and drive smarter decision-making.

Seamless integration with CRMs, marketing platforms, and AI-powered analytics eliminates data silos, making it easier to manage the entire lead-to-revenue lifecycle, improve forecasting, and enhance regulatory compliance. With NetSuite data fueling AI and machine learning models, businesses can uncover trends, predict outcomes, and automate key processes.

The real value isn’t just in storing data—it’s in using it to drive growth. Now is the time to take full advantage of your NetSuite data and turn it into a strategic asset for your business.