Low Code And High Quality Data Engineering For The Whole Organization With Prophecy Data Engineering Podcast

Summary
There is a wealth of tools and systems available for processing data, but the user experience of integrating them and building workflows is still lacking. This is particularly important in large and complex organizations where domain knowledge and context is paramount and there may not be access to engineers for codifying that expertise. Raj Bains founded Prophecy to address this need by creating a UI first platform for building and executing data engineering workflows that orchestrates Airflow and Spark. Rather than locking your business logic into a proprietary storage layer and only exposing it through a drag-and-drop editor Prophecy synchronizes all of your jobs with source control, allowing an easy bi-directional interaction between code first and no-code experiences. In this episode he shares his motivations for creating Prophecy, how he is leveraging the magic of compilers to translate between UI and code oriented representations of logic, and the organizational benefits of having a cohesive experience designed to bring business users and domain experts into the same platform as data engineers and analysts.

Announcements

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Your host is Tobias Macey and today I’m interviewing Raj Bains about Prophecy, a low-code data engineering platform built on Spark and Airflow

Interview

Introduction
How did you get involved in the area of data management?
Can you describe what you are building at Prophecy and the story behind it?
There are a huge number of