Data transformation

Data transformation converts raw, inconsistent source data into a clean, standardized, and structured format, making it ready for immediate analysis.

Data transformation is the critical 'T' in the Extract, Transform, Load (ETL) or ELT pipeline: it cleans, maps, and aggregates raw data into a unified, usable structure. This step is non-negotiable for generating quality insights, as source data is often inconsistent (e.g., varying date formats, missing fields). We leverage powerful tools like dbt (Data Build Tool) and robust SQL scripts to standardize, enrich, and restructure disparate tables into analytics-ready schemas (e.g., star or snowflake schemas). This process ensures all Business Intelligence (BI) dashboards and Machine Learning (ML) models operate from a single, trusted source of truth, directly enabling smarter, faster business decisions.

https://atlan.com/data-transformation-definition-process-examples-tools