In business intelligence, what does ETL stand for?

In the context of business intelligence, ETL stands for Extract, Transform, Load. This process is fundamental to data warehousing and analytics as it involves three key steps to handle data effectively.

• Extraction is the first step where data is collected from various source systems, which can include databases, CRM systems, flat files, and other data repositories. This step ensures that all relevant data is identified and gathered for subsequent processing.

• The next step, Transformation, involves cleaning, formatting, and altering the data to fit the operational and analytical needs of the organization. This may include processes like removing duplicates, applying business rules, and aggregating data to create meaningful datasets which are essential for reporting and analysis.

• Finally, the Load step involves moving the transformed data into a target data warehouse or database where it can be accessed and analyzed by users. This structured data can then be used for generating insights, business intelligence reports, and facilitating decision-making processes.

The other options provided do not accurately reflect the established terminology in business intelligence; they either misidentify the key components of the process or introduce non-standard terms that do not align with ETL practices. Understanding this ETL framework is crucial for anyone working with data in a business context, as it lays the groundwork for