2 Overview of Oracle Business Analytics Warehouse

This chapter provides an overview of the Oracle Business Analytics Warehouse and the Data Warehouse Administration Console (DAC).

It includes the following topics:

• Oracle Business Analytics Warehouse Overview

• Oracle Business Analytics Warehouse Architecture

Oracle Business Analytics Warehouse Overview

The Oracle Business Analytics Warehouse is a unified data repository for all customer-centric data. The purpose of the Oracle Business Analytics Warehouse is to support the analytical requirements of Oracle Business Intelligence Applications.

The Oracle Business Analytics Warehouse includes the following:

• A data integration engine that combines data from multiple source systems to build a data warehouse.

• An open architecture to allow organizations to use third-party analytical tools in conjunction with the Oracle Business Analytics Warehouse using the Oracle Business Intelligence Server.

• Prebuilt data extractors to incorporate data from external applications into the Oracle Business Analytics Warehouse.

• A set of ETL (extract-transform-load) processes that takes data from multiple source systems and creates the Oracle Business Analytics Warehouse tables.

• The DAC, a centralized console for schema management as well as configuration, administration, loading, and monitoring of the Oracle Business Analytics Warehouse.

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 2-1 illustrates how the Oracle Business Analytics Warehouse interacts with the other components of Oracle BI Applications.

Figure 2-1 Oracle Business Intelligence Applications Architecture

Oracle Business Analytics Warehouse Architecture Components

The Oracle Business Analytics Warehouse architecture comprises the following components:

• 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.

• 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.

• DAC repository. Stores the metadata (semantics of the Oracle Business Analytics Warehouse) that represents the data warehouse processes.

• Informatica Server. Also referred to as PowerCenter Services. Loads and refreshes the Oracle Business Analytics Warehouse.

• Informatica Repository Server. Also referred to as Repository Services. Manages the Informatica repository.

• Informatica Repository. Stores the metadata related to Informatica workflows.

• Informatica client utilities. Tools that enable you to create and manage the Informatica repository.