Likewise, there may be complex logic for data transformation that needs expertise. Based on the business rules, some transformations can be done before loading the data.įor Example, a target column of data may expect two source columns of concatenated data as input. #2) Transformation: Most of the extracted data can’t be directly loaded into the target system. Data extraction can be completed by running jobs during non-business hours. #1) Extraction: All the preferred data from various source systems such as databases, applications, and flat files is identified and extracted. Extraction, Transformation, and Loading are the tasks of ETL. The process which brings the data to DW is known as ETL Process. The data into the system is gathered from one or more operational systems, flat files, etc. To serve this purpose DW should be loaded at regular intervals. We all know that Data warehouse is a collection of huge volumes of data, to provide information to the business users with the help of Business Intelligence tools. College graduates/Freshers who are looking for Data warehouse jobs.Database administrators/big data experts who want to understand Data warehouse/ETL areas.Database professionals with basic knowledge of database concepts.Data warehouse/ETL developers and testers.
ETL (Extract, Transform, Load) Process FundamentalsĮTL (Extract, Transform, Load) Process Fundamentals.
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