ETL Syncler-Glossar

ETL processes are a central component of data integration and processing in data management systems. ETL stands for Extract, Transform, Load, which describes the three main phases of this process:
1. extract (Extract): In this phase, data is collected from various sources. These sources can be databases, CSV files, APIs, log files or other data stores. The aim is to identify and extract the relevant data in order to prepare it for the next phase.
2. transform: After extraction, the data is transformed into a suitable format. This may involve cleansing the data (e.g. removing duplicates or erroneous entries), converting data types, merging data sets from different sources or applying calculations and aggregations. The transformation ensures that the data is consistent and can be analyzed.
3. load: In the final phase, the transformed data is loaded into a target system, such as a CRM or ERP system or a database. The goal is to store the data in a structured and accessible way so that it can be used for analysis, reporting and other business needs.
ETL processes are particularly important for companies that want to consolidate and analyze large volumes of data from different sources. However, they also play an important role in synchronization processes between different systems due to different data models. They enable effective data integration, improve data quality and ensure that data is available on time and in the right format.