Part 5/12:
The key is incremental complexity, adapting tools and processes as needs grow, but always prioritizing cost efficiency through open-source solutions and trial periods. For example, the speaker highlights the importance of exploring options and adopting open-source tools like Grafana for visualization and Python for data processing during startup phases.
The Growing Maturity: Building Data Teams and Governance
By the third year and beyond, the startup’s data infrastructure tends to become more robust and comprehensive:
Data teams expand, typically including data engineers, data scientists, and analysts who work collaboratively.
Teams start forming clear ownership and responsibility over data assets—crucial for maintaining quality and security.