Warehouse Builder data profiling and data quality can be used alongside any third-party ETL solution or hand-coded ETL solution. Using Warehouse Builder Data Profiling with Other ETL Solutions The data profiling features of Oracle Oracle Warehouse Builder also use the infrastructure of Warehouse Builder ETL to connect to data sources, access the data to be profiled, and move intermediate profiling results into a scratch area called a profiling workspace. All required logic for the different options for handling noncompliant rows is automatically generated, for any Warehouse Builder mapping in which a data rule is used. Noncompliant rows can be routed through any data cleansing, correction or augmentation logic available in the database, transformed using ordinary mapping operators, or simply logged in the error table.
Metadata about data profiling results, represented as data rules, can be bound to the profiled data objects, and those rules are then available in any context in which the profiled objects are used in ETL.įor example, Warehouse Builder ETL can use data rules in ETL logic to implement separate data flows for compliant and noncompliant rows in a table. Where custom data cleansing and correction logic is required, it can be implemented in PL/SQL. Developers familiar with Warehouse Builder ETL features can, for example, tune performance on data cleansing processes, look at the generated code, and so on, as with any ETL mappings. Deployment, execution and scheduling for data cleansing processes is identical to other mappings. The cleansing processes are implemented by automatically created ETL mappings, with the same functionality as other ETL mappings. Warehouse Builder data quality can automatically generate data cleansing logic based on data rules. Warehouse Builder data profiling and the rest of the data quality features also derive value from and add value to Warehouse Builder ETL in the following ways: Using Warehouse Builder Data Profiling with Warehouse Builder ETL
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