Part 4/11:
The presentation traced the evolution of data systems from early days—using traditional reporting schemas and tools—to more complex, cloud-based architectures. Historically, data engineers were responsible for extracting, transforming, and loading data (ETL), followed by analysts creating reports based on predefined requirements.
Initially, business users relied heavily on engineers to prepare reports, which often led to bottlenecks. Over time, however, the rise of self-service analytics enabled users to access and analyze their data directly, democratizing data access and reducing dependence on technical teams.