As we noted in early chapters in this book, there are several reasons why a data warehouse is usually deployed in a database separated from an organization's main transactional systems. Common reasons to deploy a separate data warehouse include the desire to keep the unique resource requirements of the data warehouse segregated from transactional systems, the need to consolidate data from multiple operational systems, and the need to cleanse the data to ensure an accurate and consistent view of information.
When deploying a separate data warehouse, the data must be extracted from source systems and loaded into the data warehouse. During this process, data cleansing and consolidation can be part of a transformation process. Together, this extraction, transformation, and loading of data are commonly referred to as ETL. Understanding the data sources, determining the quality of the data, and generating and deploying the necessary ETL scripts usually consume the bulk of the time it takes to develop and initially deploy a data warehouse project.
In this chapter, we will look at how you can leverage an ETL tool, Oracle Warehouse Builder, to greatly automate the building of scripts and maintain a repository of reusable ETL maps. But first, we will take a look at the variety of data loading possibilities where the target data warehouse is deployed upon an Oracle database.
When planning a data loading strategy for your data warehouse ...