ELTtyöprosessi

ELTtyöprosessi refers to the Extract, Load, Transform (ELT) workflow, a method of data integration and processing. Unlike traditional ETL (Extract, Transform, Load) where data is transformed before being loaded into a target system, ELT loads raw data into the destination first, and then transforms it within that environment. This approach is particularly well-suited for modern data architectures like data lakes and cloud-based data warehouses, which are designed to handle large volumes of raw data and provide powerful processing capabilities.

The "Extract" phase involves pulling data from various source systems, which can include databases, applications, APIs, and files. Once extracted, the raw data is "Loaded" directly into the target data repository, such as a data lake or a cloud data warehouse. This loading process is typically faster as it bypasses the transformation step. The "Transform" phase then occurs within the target system, utilizing its computational resources. This transformation can involve cleaning, enriching, aggregating, and restructuring the data to meet specific analytical or business requirements.

The ELT model offers several advantages, including faster data ingestion, scalability, and the ability to leverage the processing power of modern cloud platforms. It also allows data scientists and analysts to work with raw data, providing greater flexibility for exploration and discovery. However, it requires a robust target system capable of handling complex transformations. The choice between ELT and ETL often depends on factors such as data volume, velocity, the target data platform, and the complexity of the required transformations.