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SuiteWorld October 6 - 9, 2025: Agenda Builder is live!
Read on for the latest updates including:
• Agenda Builder launch
• SuiteWorld On Air registration
• New NetSuite Prompt Studio Contest
• And more!
Check out this thread to learn more!
Read on for the latest updates including:
• Agenda Builder launch
• SuiteWorld On Air registration
• New NetSuite Prompt Studio Contest
• And more!
Check out this thread to learn more!
Going to SuiteWorld? Connect with SuiteGurus—Your NetSuite Product Experts!
Don’t miss your chance to meet our SuiteGurus—NetSuite Support professionals and subject matter experts with extensive experience in select product areas, including OneWorld, Advanced & Basic Accounting, Supply Chain Management, Receivables & Payables, CRM, Account Administration, and the SuiteCloud Platform. Full Conference attendees can prebook exclusive 30-minute one-on-one sessions for your product questions.
Spots are limited! Register through your Agenda Builder and find SuiteGuru under Agenda Enhancements.
Don’t miss your chance to meet our SuiteGurus—NetSuite Support professionals and subject matter experts with extensive experience in select product areas, including OneWorld, Advanced & Basic Accounting, Supply Chain Management, Receivables & Payables, CRM, Account Administration, and the SuiteCloud Platform. Full Conference attendees can prebook exclusive 30-minute one-on-one sessions for your product questions.
Spots are limited! Register through your Agenda Builder and find SuiteGuru under Agenda Enhancements.
Connect and Query NSAW with Python
Python is a programming language which is commonly used for data processing tasks. For example, Python can be used to extract data from an API or database, transform and cleanse data, for data science projects, or for data analysis. While it takes some learning to be comfortable, it is a widely used language and there are a vast array of resources available online for learning.
Why use Python with NSAW? Some example use cases:
- Extract data from another application, transform the data, and load into the NSAW data warehouse (ETL)
- Query the NSAW data warehouse and use Python libraries like Scikit-Learn or Pandas for data science projects with your NS data
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