ELTtyöprosesseista

ELTtyöprosessi, or ELT workflow, refers to the modern data integration and transformation process known as Extract, Load, Transform. This approach contrasts with the traditional ETL (Extract, Transform, Load) method. In an ELTtyöprosessi, raw data is first extracted from various sources and then loaded directly into a target data warehouse or data lake. The transformation of this data, such as cleaning, enriching, or structuring it, happens *after* it has been loaded into the target system.

The primary advantage of the ELTtyöprosessi is its ability to leverage the powerful processing capabilities of modern cloud-based data warehouses and data lakes. This allows for faster data ingestion and the ability to handle larger volumes of data more efficiently. Furthermore, by loading raw data first, organizations maintain a complete historical record of their data, which can be valuable for future analysis or re-processing with different transformation rules.

Key components of an ELTtyöprosessi include data sources (databases, APIs, files), a staging area (often the target data warehouse itself), and a transformation engine (typically SQL-based tools or specialized ELT platforms). This workflow is particularly well-suited for big data environments and scenarios where agility in data analysis is paramount. It enables data analysts and scientists to access and transform data on demand, fostering a more flexible and iterative approach to business intelligence and data science.