The data lakehouse is the latest evolution in big data architecture, combining the reliability of data warehouses with the scalability of data lakes. A key enabler of this paradigm is the open table format, which provides transactional consistency, schema evolution, and efficient data management. Apache Iceberg has emerged as the most advanced and widely adopted open table format solution, addressing critical challenges such as inefficient partitioning, lack of ACID compliance, and the absence of SQL-native analytics in traditional data lakes. It is a disruptive and transformative technology which is redefining the landscape of large-scale data management. Iceberg reintroduces SQL query efficiency at scale, eliminates vendor lock-in by supporting multiple processing engines, and enables time travel for historical data access. Its zero-copy architecture optimizes storage while maintaining a single source of truth for enterprises. This paper provides an in-depth analysis of Iceberg’s technical foundations, its advantages over other table formats, and its transformative role in modern data lakehouse architecture. Through detailed exploration and real-world use cases, we demonstrate how Iceberg is redefining data engineering and driving the future of scalable, cost-effective data architectures in the form of data lakehouse.