We are in the midst of a silent yet profound transformation in the world of Business Intelligence. For years, companies have invested millions in visualization tools, data warehouses, and analyst teams, but they faced a persistent problem: the cost of maintaining and scaling these platforms grew exponentially, while the quality and consistency of insights deteriorated.
The arrival of Google Cloud, specifically BigQuery and Looker, promised to solve these challenges. However, we have seen in real projects that technology alone is not enough. Without a well-designed architecture that integrates FinOps practices and a robust semantic layer, organizations simply migrate their problems to the cloud, often amplifying them.
"The future of BI is not about processing more data, but about processing the right data, in the right way, at the right cost."
— Martín Vélez, CTO RavencoreXIn this first edition of RavencoreX MAG, we share the accumulated experience from real implementations for LATAM companies. You will see proven architectures, real code, measurable results, and most importantly, lessons learned that will save you months of iteration and thousands of dollars in avoidable costs.
This is not a theoretical tutorial. It is a battle manual for data teams looking to build scalable, governed, and economically sustainable BI platforms.