The Iceberg Summit 2025 – New York
Talk: Best Practices for Schema Evolution in Apache Iceberg: Making Your Data Future-Proof
Date: April 2025
Description: One of the most powerful features of #ApacheIceberg is its ability to evolve schemas without breaking existing queries. Unlike traditional data lake architectures that require table rewrites or migrations, Iceberg allows seamless adding, renaming, and modifying columns while maintaining query efficiency. In this session, we’ll explore best practices for schema evolution, including: When and how to add new columns safely. Handling data type changes without breaking downstream applications. The impact of renaming or dropping columns on query performance. Real-world case studies on schema evolution strategies in production. By the end of this talk, attendees will gain a clear understanding of how to design flexible and future-proof schemas that scale with changing business needs.
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Beam Summit 2025
Talk: Build Seamless Data Ecosystems
Date: May 2025
Description: Modern data architectures are no longer built around a single tool — they thrive on interoperability and community-driven integration. This session explores how Apache Beam serves as the flexible processing engine that connects streaming platforms like Kafka with modern, ACID-compliant data lakehouse solutions like Apache Iceberg. Through real-world architecture patterns and practical examples, we’ll dive into how organizations are using Beam to unify disparate data sources, enable real-time and batch analytics, and future-proof their data platforms. You’ll also gain insights into how the open-source community continues to drive innovation across this ecosystem — from new connectors to performance optimizations and beyond. Whether you’re designing pipelines, modernizing ETL, or exploring community-powered tooling, this session gives you the blueprint to build scalable, production-ready data ecosystems with confidence.
Data Summit 2025
Talk: Future-Proofing Data Warehousing
Date: May 2025
Description: In discussing future-proofing data warehousing, Vayyala considers the impact of data modeling, medallion architecture, and integration. Building an enterprise data warehouse is more than just a technical challenge; it’s a strategic investment in a company’s future. Implementing a robust, scalable, and flexible EDW ensures that an organization has the data it needs to make informed, data-driven decisions.
Devup 2025
Talk: Democratizing Data: Empowering Your Organization with Cloud Data Management
Date: August 2025
Description: In this session, I talked about
Data Democratization
•Benefits
•Challenges
•Strategy
•Real world example
•Data Lake Architecture
•Building a Data-Driven Culture
Data Toboggan – Cool Runnings 2025
Semantic Layers in the Lakehouse: Simplifying Data Access Without Sacrificing Control
In the era of data democratization, organizations are striving to make data both accessible and governed. Enter the semantic layer—the unsung hero that abstracts technical complexity while enforcing consistency and security. In this lightning talk, you’ll learn how semantic layers simplify analytics for end users while anchoring enterprise-wide trust in data.
We’ll cover:
What a semantic layer is (and isn’t)
How it fits into modern lakehouse architectures (e.g., in Microsoft Fabric or Databricks)
A quick real-world example (Power BI model or metrics layer)
Key benefits: faster insights, fewer errors, scalable governance
Perfect for data architects, BI professionals, and anyone enabling self-service analytics in a cloud-first world.
The Azure and AI Show
Talk: Future-Proofing Enterprise Data Warehousing: Medallion Architecture, Modern Modeling, and Scalable Integration
Date: October 2025
Description: In this session, I will explores how organizations can future-proof their data platforms by combining modern data modeling principles, Medallion Architecture, and seamless integration strategies.
Building an enterprise data warehouse is no longer just a technical milestone—it’s a strategic capability that defines an organization’s agility, governance posture, and ability to support analytics and AI at scale. This talk outlines practical patterns for designing scalable, resilient, and business-aligned EDW architectures that evolve with changing data demands, while ensuring trust, reusability, and long-term adaptability.
Insights on Data & AI 