Data Load - Full Vs Incremental #dataintegration #etltesting #trending #dataintegration

This video explains the difference between full load and incremental load in ETL (Extract, Transform, Load) data integration processes. Here's a summary: Full Load (0:37, 1:48): This strategy involves completely replacing all existing data in the target table with new data from the source every time. It's best used when data volume is small, source data is unpredictable, or for one-time activities, like loading static lookup tables (e.g., country, product, store data). Incremental Load (0:39, 3:35): This method only transfers new or changed records from the source system to the target table since the last successful data load. It's highly efficient for large volumes of data and frequently updated information, often tracked using timestamps or version keys. Examples include sales fact tables or daily customer data.