Oracle Business Analytics Warehouse Architecture

High-level analytical queries, like those commonly used in Oracle Business Analytics Warehouse, scan and analyze large volumes of data using complex formulas. This process can take a long time when querying a transactional database, which impacts overall system performance.

For this reason, the Oracle Business Analytics Warehouse was constructed using dimensional modeling techniques to allow for fast access to information required for decision making. The Oracle Business Analytics Warehouse derives its data from operational applications, and uses Informatica’s data integration technology to extract, transform, and load data from transactional databases into the Oracle Business Analytics Warehouse.

Figure illustrates how the Oracle Business Analytics Warehouse interacts with the other components of Oracle BI Applications.

The Oracle Business Analytics Warehouse architecture comprises the following components:

1. DAC Client. A command and control interface for the data warehouse to allow for schema management, and configuration, administration, and monitoring of data warehouse processes. It also enables you to design subject areas and build execution plans.
2. DAC Server. Executes the instructions from the DAC Client. The DAC Server manages data warehouse processes, including loading of the ETL and scheduling execution plans. It dynamically adjusts its actions based on information in the DAC repository. Depending on your business needs, you might incrementally refresh the Oracle Business Analytics Warehouse once a day, once a week, once a month, or on another similar schedule.
3. DAC repository. Stores the metadata (semantics of the Oracle Business Analytics Warehouse) that represents the data warehouse processes.
4. Informatica Server. Also referred to as

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