Stage 1 · Lesson 2 of 8
The data lifecycle
Almost every data platform follows the same , the path data takes from birth to use. First, data is generated in source systems, such as an app database, a payment provider or a sensor. Next it is ingested: copied into your platform, either on a schedule or as a steady stream.
Then it is stored, usually as files in (cheap cloud file storage) and as tables in a warehouse. After that it is transformed: cleaned, joined, stripped of duplicates and shaped into useful tables. Finally it is served to dashboards, machine learning models, or syncs, which push data back into business tools.
Security, data quality, (running steps in order) and cost sit underneath every step. Use this lifecycle as the map for the rest of the roadmap, because each stage goes deeper into one part of it.
Common trapdesigning from the tool outward instead of starting from what the final user needs and how fresh it must be.
A question to check yourself, an AI practice session and 1 cheat sheet entry come with the full roadmap. Unlock
Resources for this stage
Start with· follow one of these
- CourseFreeData Engineering Zoomcamp
DataTalks.Club · Beginner
Free, cohort-based or self-paced course: Module 1 covers Docker, PostgreSQL and loading real taxi data
- CourseFreeCS50's Introduction to Programming with Python
Harvard University · Beginner
If your Python is shaky, work through the lectures on functions, exceptions, file I/O and libraries first