Welcome to the Webinar Series: Towards Data Lakehouse Architecture
Model Context Protocol (MCP), spec-driven development (SDD) and conversational data interfaces are rewriting the data engineering playbook.
In this episode of the Towards Data Lakehouse Architecture series, we’ll explore how Agentic AI shifts data teams from hand-built pipelines to outcome-driven data products guided by clear intent and intelligent assistants.
You’ll learn how MCP integrations enable AI assistants to tap your data catalogs, databases and transformation tools like dbt - dramatically accelerating development while preserving governance and trust.
We’ll show how spec-driven development turns business needs and technical requirements into unambiguous, testable data products - boosting delivery speed and confidence. Finally, we’ll explore conversational data interfaces that allow both technical and business users to interact with data products using natural language.
In this session, you will learn:
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How MCP enables AI assistants to work across your data stack
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How SDD improves data product quality and delivery speed
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How conversational interfaces bridge the gap between business and data teams
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What AI-assisted engineering means for modern Data Lakehouse architectures
This webinar is for data professionals who want to spend less time on boilerplate and more time shaping outcomes that matter.
When: January 27, 15:00 CEST; 14:00 BST; 09:00 EDT
Duration: 1h, Online on Zoom
Meet the Speakers:
Marek Wiewiórka
Chief Data Architect, Xebia
Assistant at Warsaw University of Technology
Marek is a seasoned Big Data and Cloud Architect with 15+ years of experience in designing and implementing modern data and MLOps platforms. Currently, he is the Chief Data Architect at Xebia, and a Research Assistant at Warsaw University of Technology, putting the finishing touches to his PhD dissertation. Privately - a keen long-distance runner, gravel bikes enthusiast, and absolutely in love with the Italian Lakes!
Mateusz Pytel
Data Architect, Xebia
Cloud and MLOps Architect with over 15 years of experience in data architecture, advanced analytics, and machine learning operations. His expertise lies in building scalable, cloud-native Data/AI/ML platforms that simplify the journey from prototype to production. He specializes in MLOps and GenAI, designing solutions that automate ML lifecycles, reduce operational costs, and accelerate knowledge discovery.
Toward Data Lakehouse Architecture
Data Lakehouse seems to be a new buzzword; everyone wants it, but does everyone need it? In many cases, Data Lakehouse will be a perfect solution, but not always, and not just any Data Lakehouse. In this Webinar Series, we want to get closer to the Data Lakehouse concept, what problems it addresses, and how to design its architecture to make it the holy grail.
Watch previous TDLA Webinars and discover the concept of Open Data Lakehouse.