Part 6/12:

The data team tackles various challenges, including analyzing the success of sales campaigns, marketing efforts, and operational metrics, within tight timeframes—sometimes mere minutes. To meet these demands, the platform leverages cutting-edge data processing solutions—primarily utilizing solutions like Spark, Trino, and Kafka—while emphasizing an open-source, scalable, and flexible architecture.

Evolving Data Architecture: From Limitations to Scalability

Initially, the platform had a third-party data platform architecture that relied on traditional batch processing. However, limitations such as high costs, inefficient resource utilization, and inability to process large-scale real-time data prompted a strategic overhaul.