The Fifth Elephant 2026 Annual Conference

Workshop Overview
Modern data platforms are built in layers—from how data is stored, to how it is managed, and finally how different tools discover and access it. In this workshop, we’ll walk through that journey together.
We’ll start by looking at modern columnar file formats like Parquet and Apache Arrow, understanding why they became the standard for analytics and how they differ from traditional row-based formats. From there, we’ll explore open table formats such as Apache Iceberg and Delta Tables, and see how they solve challenges like ACID transactions, schema evolution, and time travel. Finally, we’ll discuss the role of catalogs, why they matter, and how solutions like Apache Polaris ,Hive Catalog and Unity Catalog enable governance and interoperability across multiple compute engines.
The workshop will combine concepts with practical demonstrations so that participants not only understand the “what” but also the “why” behind these technologies.
Key Takeaways
By the end of the workshop, participants will:
Understand the differences between row-based and columnar storage formats and why columnar storage is preferred for analytics.
Learn how Parquet and Apache Arrow are designed for efficient data processing.
Understand why table formats like Iceberg and Delta Tables exist and the problems they solve.
Explore features such as ACID transactions, schema evolution, partition evolution, and time travel.
Learn the purpose of catalogs and how they help with metadata management, governance, and interoperability.
Leave with a clear understanding of how files, table formats, and catalogs fit together in a modern lakehouse architecture.
Who Should Participate
The workshop is aimed at:
Data Engineers
Analytics Engineers
Data Platform Engineers
Backend and Software Engineers working with data infrastructure
Database Engineers and Architects
Students or professionals interested in learning about modern data platforms
Background Knowledge Requirements
Required
Basic SQL
Familiarity with files and tabular data
Comfort using the command line
Nice to Have (not mandatory)
Exposure to Spark, Trino, DuckDB, or similar query engines
Basic understanding of data lakes or cloud object storage
No prior experience with Table formats and Catalogs is required.
Software Installation Prerequisites
Participants should have the following installed before the workshop:
Docker Desktop (or Docker Engine)
I’ll share the detailed setup instructions and workshop repository before the session.
Workshop Plan

1. Columnar File Formats
   Row-based vs. columnar storage
   Parquet and Apache Arrow
   Compression and encoding
2. Open Table Formats
   Why managing data as files isn’t enough
   Apache Iceberg and Delta Tables
   ACID transactions, snapshots, schema evolution, and time travel
   Hands-on examples
3. Catalogs
   Why catalogs are needed
   Metadata management and governance
   Apache Polaris , Hive Catalog and Unity Catalog
   Bringing everything together with an end-to-end workflow
   We’ll wrap up with a Q&A and discussion on real-world adoption and best practices.
   .