Hi @boitumelodikoko 

A few more principles I always share with people entering the data space:

Observability is non-negotiable.

• If you can’t see what your pipelines are doing, you can’t fix what breaks.
• Good logging, metrics, and alerts save countless hours and prevent silent failures.

Document as you build, not afterward.

• Clear explanations, consistent naming, and simple diagrams make your work usable for others and for your future self.

Keep pipelines modular and predictable.

• Small, focused components are easier to test, reuse, and debug.
• Monolithic notebooks filled with hidden logic are where most long-term problems begin.

Treat data quality as a first-class citizen.

• Constraints, schema checks, and validation rules prevent bad data from cascading into bigger issues downstream.