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

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

• Hello and welcome to the Data Engineering Podcast, the show about modern data management
• You listen to this show to learn about all of the latest tools, patterns, and practices that power data engineering projects across every domain. Now there’s a book that captures the foundational lessons and principles that underly everything that you hear about here. I’m happy to announce I collected wisdom from the community to help you in your journey as a data engineer and worked with O’Reilly to publish it as 97 Things Every Data Engineer Should Know. Go to dataengineeringpodcast.com/97things today to get your copy!
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• Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems. No more scripts, just SQL. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Get started for free at dataengineeringpodcast.com/hightouch.
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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 tools and recommended architectures for every variety of data need. Why is data engineering still such a complicated and challenging undertaking?
  • What features and capabilities does Prophecy provide to help address those issues?
• What are the roles and use cases that you are focusing on serving with Prophecy?
• What are the elements of the data platform that Prophecy can replace?
• Can you describe how Prophecy is implemented?
  • What was your selection criteria for the foundational elements of the platform?
  • What would be involved in adopting other execution and orchestration engines?
• Can you describe the workflow of building a pipeline with Prophecy?
  • What are the design and structural features that you have built to manage workflows as they scale in terms of technical and organizational complexity?
  • What are the options for data engineers/data professionals to build and share reusable components across the organization?
• What are the most interesting, innovative, or unexpected ways that you have seen Prophecy used?
• What are the most interesting, unexpected, or challenging lessons that you have learned while working on Prophecy?
• When is Prophecy the wrong choice?
• What do you have planned for the future of Prophecy?

Contact Info

• LinkedIn
• @_raj_bains on Twitter

Parting Question

• From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

• Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
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Links

• Prophecy
• CUDA
• Apache Hive
• Hortonworks
• NoSQL
• NewSQL
• Paxos
• Apache Impala
• AbInitio
• Teradata
• Snowflake
  • Podcast Episode
• Presto
  • Podcast Episode
• LinkedIn
• Spark
• Databricks
• Cron
• Airflow
• Astronomer
• Alteryx
• Streamsets
• Azure Data Factory
• Apache Flink
  • Podcast Episode
• Prefect
  • Podcast Episode
• Dagster
  • Podcast Episode
  • Podcast.__init__ Episode
• Kubernetes Operator
• Scala
• Kafka
• Abstract Syntax Tree
• Language Server Protocol
• Amazon Deequ
• dbt
• Tecton
  • Podcast Episode
• Informatica

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA