From Data Chaos to Control: How a Global Telco Tamed Petabyte-Scale Challenges with Apache Iceberg

When a leading telecommunications operator hit the scaling wall with their legacy Hive infrastructure, managing petabyte-scale customer data across billions of records became untenable. Their IDPR workloads suffered from slow queries, rising storage costs,partition explosion, and schema changes that broke downstream systems.

This session explains why they chose Apache Iceberg and how it transformed their architecture, including the business and technical decision criteria used to select Iceberg over other open table formats

Key Takeaways: Why Iceberg: ACID guarantees, hidden partitioning, time travel, interoperability, and the executive case that secured buy-in Architecture & Best practices: A high level architecture plus Cloudera-recommended patterns for Iceberg + Impala, partitioning strategies, compaction policies, metadata optimization, and query engine tuning for workloads Measurable Impact: Faster queries, significant storage and infrastructure cost reductions, simpler operations, and improved regulatory compliance.

Speakers:

Attila Turóczy: Senior Director of Engineering at Cloudera

Apache Hive, Impala and Big Data enthusiasm at Cloudera