Oracle OBIEE and pre-built Analytics (Siebel) Architecture

This posting won't focus on the build it vs buy it thought process (which is valid considering these nice pre-built analytics solutions really cost a bundle!). Instead I wanted to first discuss OBIEE and Oracle E-Business suite or Oracle Apps integration. Now, there should be no mystery that a huge amount of operational data is flowing through your Oracle apps database. It should also be no mystery that you'd probably like to get as much value out of that data and see what it contains...forecasting, trending, historical data...you name it. That's where BI and OBIEE really come in.

Now with OBIEE, you can have a world class operational system with APPS and a world class BI and data warehousing solution using OBIEE. The big sticky here is what do we do? Custom develop the whole underlying architecture to get OBIEE up and running? We're definitely not going to report off of the apps database with our analytic reports! We need a solid data warehousing environment, data marts, and strong ETL to get the right data out of apps, and into our Data Warehouse. THEN we can consider OBIEE and its reporting capabilities.

You might however consider using the pre-built analytics that can be purchased. These can roll-up lots of reports, pre-built ETL, and many DW structures that are already there for your deployment. The typical client will be able to immediately use 60-80% of this pre-built package right out of the box. So what does this all look like from a bird's eye view? Well let us JUST look at the concept of the pre-built analytics below:

High-level analytical queries, like those commonly used in Oracle BI, 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 the transactional database into the Oracle Business Analytics Warehouse.
The Oracle Business Analytics Warehouse architecture comprises the following components:

DAC client. A command and control interface for the data warehouse to allow for set up,
configuration, administration, and monitoring of data warehouse processes.

DAC server. Executes the instructions from the DAC client. The DAC server manages data
warehouse processes, including scheduling, loading of the ETL, and configuring the subject areas
to be loaded. 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. When the server is loading or refreshing the Oracle Business Analytics
Warehouse, it is recommended that the server be dedicated to that activity. However, when the
ETL server is not loading or refreshing the Oracle Business Analytics Warehouse, you can use it
for other purposes.

Informatica Repository Server. Manages the Informatica repository.

Informatica Repository. Stores the metadata related to Informatica workflows.

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