The lifecycle's stages say what happens to data. The undercurrents say how well it happens. They are the practices that apply at every stage, and they separate a pipeline that runs from a platform people trust.
| Undercurrent | The question it answers | Taught in |
|---|---|---|
| Security | Who can see and change this data? | 1.14, 4.16, 5.15, 6.14, 7.17, 8.14 |
| Data management | Is it documented, correct, governed? | 8.11-8.13 |
| DataOps | Can we change it safely and notice failures? | 7.15, 8.11-8.12 |
| Data architecture | Will the design survive growth and change? | 1.6, 1.9, Lakehouses, Data Quality and Governance |
| Orchestration | Does each step run in order and on time? | Orchestration and Pipelines |
| Software engineering | Is the code tested, reviewed, versioned? | Every chapter |
Software engineering runs through the whole book rather than one section: every pipeline you build is code, kept in Git 1,932 , tested and reviewed like any application (Package Managers and DevOps covers the Git and CI tooling).