LIVE WEBINAR
Accelerating Analysis with LLM drafted Python Data Pipelines using JMP
Date: 5 May, Tuesday
Time: 1:00-1:45 p.m. (Malaysia and Singapore) | 10:30-11:15 a.m. (India) | 3:00-3:45 p.m. (Australia)
Presenter: Liang HUANG
Location: Zoom Live Webinar
Registration: Free
Engineering teams are under increasing pressure to turn growing volumes of data into insights quickly and consistently. Many engineers using analytics tools, however, are not full-time programmers. This webinar introduces a practical approach that bridges that gap: using Large Language Models (LLMs) to help draft simple Python data pipelines that prepare engineering data for analysis in JMP.
Instead of building complex codebases, augmented workflows can create lightweight, reusable data preparation steps that feed directly into JMP. The result is a more sustainable analytics process that reduces repetitive manual work, improves consistency across projects, and enables engineers at any coding level to move from raw data to decision-ready insights.
In this webinar, learn how to:
- Use LLMs to draft practical Python workflows for preparing engineering datasets
- Build reusable data ingestion templates for consistent, future-ready data pipelines
- Connect Python-processed data with JMP analytics to accelerate insight generation
- Automate recurring analysis and reporting with minimal scripting effort
This session is ideal for engineers, analysts, and technical teams looking to modernize their analytics workflow without requiring advanced programming skills.