Explore the limitations of traditional ETL scripts and discover how AI-powered agents offer a more flexible, resilient, and intelligent approach to data transformation pipelines.
Tired of complex JQ queries or custom code? Learn how to restructure, clean, and manipulate complex JSON objects using simple, human-readable instructions with an API call.
A step-by-step tutorial showing how to take messy raw data and instantly transform it into a clean, structured format using the transform.do agent and just a few lines of code.
Dive deep into the 'Data as Code' philosophy. Learn how treating your data transformations as version-controlled, API-driven instructions leads to better governance and reusability.
Messy data is a silent killer of productivity. See how you can build automated data cleaning pipelines that handle inconsistent formats, typos, and duplicates effortlessly.
Go beyond one-off transformations. Learn how to define and deploy a production-ready data transformation 'Service-as-Software' for consistent, repeatable business logic.
Forget parsing libraries and boilerplate code. This guide shows how to integrate the transform.do agent to reliably convert CSV data to structured JSON with a single API call.
Don't let data preparation be a bottleneck. Learn how empowering teams with easy-to-use data transformation tools accelerates analytics, reporting, and development cycles.
Flattening, nesting, and renaming keys in complex JSON objects can be a headache. See how an AI agent can interpret your desired structure and perform the changes automatically.
We compare the speed, flexibility, and maintenance overhead of using an AI transformation agent versus writing and maintaining custom Python scripts for data processing tasks.