ETL is a data processing method used to collect, organise and transfer data in a structured and systematic manner. In this process, data is extracted from source systems, transformed into a suitable format and loaded into a target system.
Data is often generated in different formats, structures and locations. To analyse and interpret this information effectively, it must be consolidated into a common environment and standardised format. Without this standardisation, analytical processes may become complex, time-consuming and costly.
ETL provides significant advantages in terms of both cost and operational efficiency. It makes data more accessible, consistent, valuable and meaningful for analysis. ETL processes are commonly used in data migration, system integration, business intelligence and data warehousing projects.
ETL stands for Extract, Transform and Load. The process consists of these three stages and is generally designed around a target storage environment, such as a data warehouse, data lake or centralised database.
The stages of an ETL process can be summarised as follows:
Extract: This is the process of retrieving data from source systems such as databases, file systems, applications and web services. Relevant data is selected and collected from tables, files or other sources. At this stage, the objective is to extract the data securely, accurately and in an appropriate format.
Transform: This is the stage in which extracted data is converted into a format suitable for the target system. The data may be cleaned, standardised, validated, reorganised or combined with information from other sources. Transformation is essential because it enables data from different systems to be analysed and evaluated consistently. Common operations include data type conversion, value standardisation, filtering, aggregation, calculation and data merging.
Load: This is the stage in which the transformed data is transferred to the target system. The data may be loaded into databases, data storage platforms, data warehouses or other analytical environments. During this stage, controls are applied to ensure that the data is transferred securely, accurately and completely.
