IBM Data Science Test 2025 – 400 Free Practice Questions to Pass the Exam

The acronym ETL stands for "Extract, Transform, Load," which is a fundamental process in data warehousing and data integration.

In this process, "Extract" refers to the initial step where data is collected from various source systems. These sources can include databases, APIs, flat files, or any other format containing data. The goal during this stage is to gather relevant and accurate data.

"Transform" involves the processing of the extracted data to convert it into a suitable format or structure for analysis. This step may include cleaning the data (removing duplicates, correcting errors), aggregating data, or applying business rules to prepare it for analysis or reporting.

Finally, "Load" is the step where the transformed data is loaded into the target system, which is typically a data warehouse or a data lake. This makes the data available for querying and analysis, enabling organizations to derive insights from it.

Understanding the ETL process is crucial for anyone involved in data analysis or data engineering, as it lays the groundwork for effective data management and utilization.