Definition
ELT, or Extract Load Transform, is a data integration process where raw data is first moved from its source systems into a target data store, typically a cloud data warehouse or data lake. Once the data resides in the target environment, transformations are applied using the processing power of the target system. This approach leverages the scalability and performance of modern cloud data platforms to handle large volumes of data efficiently. ELT is crucial for enabling advanced analytics, business intelligence, and machine learning initiatives by making data readily available for complex analysis. For instance, a retail company might use ELT to load sales transaction data from various stores into a cloud data warehouse for immediate analysis of purchasing trends. It differs from ETL (Extract Transform Load) by delaying the transformation step until after the data is loaded, which is often more efficient for big data scenarios. You will encounter ELT concepts on AWS certification exams like the AWS Certified Solutions Architect Associate.