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Before you can run your application on an Oracle database, you need to populate your database. One of the most common sources of database data is a set of flat files from legacy systems or some other source. Traditionally, using the conventional or direct data load method with SQL*Loader was the only way to load this data from the external files into database tables. SQL*Loader is still technically the main Oracle-supplied utility to load data from external files, but you can also use the external tables feature, which employs the SQL*Loader tool to help you access data located in external datafiles. Because the raw data may contain extraneous information or data in a different format from what your application needs, you frequently need to transform the data in some way before the database can use it. Transforming data is an especially common requirement for data warehouses, which extract their data from multiple sources. It s possible to do some preliminary or basic transformation of the raw data during the SQL*Loader run itself. However, more complex data transformation requires separate steps, and you have a choice of several techniques to manage the transformation process. Most warehouse data goes through three major steps before you can analyze the data: extraction, transformation, loading (ETL). These steps are defined as follows:

Extraction is the identification and extraction of raw data, possibly in multiple formats, from several sources, not all of which may be relational databases Transformation of data is the most challenging and time consuming of the three processes Transformation of data may involve the application of complex rules to data It may also include performing operations such as data aggregation and the application of functions to the raw data Loading is the process of placing the data in the database tables This may also include the task of maintaining indexes and constraints on the tables Traditionally, organizations have used two different methods of performing the ETL process: the transform-then-load method and the load-then-transform method In the former method, the data is cleaned or transformed before it s loaded into Oracle tables Custom-made ETL processes are usually used for the transformation of data.

In the first case, there really is no way to break the coupling, short of redesigning A. If A is derived from B, it was probably designed that way for a reason. If you didn t design A yourself, you might want to think twice before refactoring A s ancestry. Changing the base class of a class is not something you should attempt without proper forethought, especially if the sole goal is to reduce coupling. Inheritance always causes UTC, and there is no way around it. In the second case, there are ways to change UTC into ATC. Let s look at a simple example, with a class A that does nothing except create an instance of B and invoke a method. Figure 1-43 shows the class diagram of the system.

In the latter method of data cleansing, you aren t fully taking advantage of Oracle s built-in transformation capabilities in most cases In the load-thentransform method, the raw data is first loaded into staging tables and moved to the final tables after the data transformation process is performed within the database itself Intermediate staging tables are the key to the load-then-transform method The drawback to this technique is that you must maintain multiple types of data in the table, some in a raw and original state and some in a finished state Oracle Database 11g offers terrific ETL capabilities that enable a newer way to load data into a database: the transform-while-loading method By using the Oracle database to perform all the ETL steps, you can efficiently perform the typically laborious ETL processes.

Oracle provides you with a whole set of complementary tools and techniques aimed at reducing the time needed to load data into the database while simplifying the work involved Oracle s ETL solution includes the following components: External tables: External tables provide a way to merge the loading and transformation processes Using external tables will enable you to eliminate cumbersome and time-consuming intermediate staging tables during data loading External tables are discussed in the Using External Tables to Load Data section in this chapter Multitable inserts: Using the multitable insert feature, you can insert data into more than one table at the same time, using different criteria for the various tables This capability eliminates the additional step of first dividing data into separate groupings and then performing data loading Multitable inserts are discussed in the Using Multitable Inserts section in this chapter.