Data Normalization

Data normalization is the process of converting data from different sources or formats into a consistent representation, removing inconsistencies that prevent data from being compared or processed together.

Common normalization tasks include standardizing date formats (all dates as ISO 8601 strings), unifying currency representation (all prices as numbers in a single currency), resolving naming differences (one source calls it 'sqft', another calls it 'area'), and converting units.

When building systems that ingest data from multiple API sources, normalization is a required ETL step. Defining a canonical schema before writing your pipeline makes normalization a deliberate, documented step rather than an afterthought.