What is ETL?

Data integration is crucial for modern businesses as it enables them to consolidate data from various sources into a central platform and generate actionable insights. The process involves extracting data, transforming it into a standardized format, and loading it into a data warehouse. This procedure is facilitated by ETL (Extract, Transform, Load) which has been around since the 1970s but is now evolving to meet the demands of an increasingly cloud-based business environment. Traditional ETL systems face challenges such as unscalable architecture, labor effort and fragile workflows due to their on-premise nature and complex engineering requirements. However, with the advent of cloud technology, ELT (Extract, Load, Transform) has emerged as a more scalable solution that allows data transformation within the data warehouse environment using SQL. ELT is fully managed by service providers, eliminating the need for businesses to design, build or manage hardware and infrastructure for data integration. It also simplifies labor effort by automating data pipeline management and offering standardized commodity schemas across different sources. Moreover, it enhances workflow robustness as there's no longer a need to rebuild entire pipelines when data sources or business needs change. In addition to ELT, Reverse ETL has also emerged, enabling businesses to operationalize data by syncing transformed data from data warehouses into operational systems and tools such as CRMs and ERPs. As data continues to play a central role in enterprises, the significance of data integration will only grow, with newer cloud data technologies continuing to shape its evolution.