Session Abstract

With the rise of the Modern Data Platforms, much time has been spent on discussions about tech stacks (e.g. Airflow, dbt, Great Expectations, among others) and new approaches, such as data lakehouse, data mesh, and Reverse ETL.

However, even with the existence of a diverse ecosystem of tools and methodologies, data pipelines remains a partially solved issue – which should’ve been solved by now! Data Engineers still struggle regarding integrating different tools, and avoiding reinventing the wheel each time a new pipeline is required.

With that in mind, we at Dotz Inc. developed Debussy: a low-code data engineering framework, that aims to be easy to use and extensible, while following the best practices of OOP and each underlying tool.

In this presentation I’ll give an architectural overview of Debussy and discuss how it can help in building a Modern Data Platform while empowering data engineers, as well as data scientists and analysts with a self-service approach.


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Lawrence Fernandes


Lawrence Fernandes is a consultant, author, and keynote speaker focused on Big Data architecture. He is currently the Lead Data Architect at Dotz Inc., a leading loyalty platform in Brazil, whose partners include Ant Group, the financial arm of chinese giant Alibaba. He holds a BSc Computer Science degree from CEFET/RJ and is working towards a Solutions Architect MBA at PUC-Minas.

With a background in database administration, business intelligence and data engineering, his career expands over several industries, including broadcasting, telecommunications, petroleum, consulting services, consumer packaged goods, e-commerce, finance and banking.

Lawrence worked his way up from an entry-level position to a top-performing data expert within Fortune 500 and startup companies, bringing a track record of integrity, creativity, and passion to every project – oh, as an amateur musician and metalhead, he also brings his electric guitars!

Social media links

How did you originally get involved with data architecture and / or data engineering

Working at IBM, where I was involved with Data Warehousing projects and discovered the fascinating world of data architecture.

What one data architecture or data engineering book would you take to a desert island. Please give a brief description of the book, and why it stands out.

The Data Webhouse Toolkit. I’m a huge fan of Kimball Group and their books, and that’s the only one I didn’t have time to read completely. Also, it fascinates me that this book was published in 2000 and was already dealing with clickstream data – Ralph Kimball was way ahead of it’s time!

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