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Monday, 23 September 2013


By on September 23, 2013

OBIA (Oracle Business Intelligence Applications)

Pre Built ETL process and tools use to configure, modify, handle, examine and maintaining the Database Warehouse Console.

ETL Process means extracting the data from various types of sources and transforming to staging area of warehouse.

Some data sources will require very little or even no manipulation of data.

The transform stage applies a cycle of rules or functions to the extracted data from the source to derive the data for loading into the end target.

In the load stage, it loads the data into the end target, usually the data warehouse (DW). Depending on the requirements of the organisation, this process varies widely


Some of the pre built ETL Components are

Mappings and work flows in informatica are prebuilt for OBIA for various types of data sources.

Repository and Integration services of informatica are prebuilt process for the OBIA applications in the informatica mappings and work flows.

Each Source system has different mapping and mapplets, work flows definition in informatica.

ETL Informatica tool is used to edit, configure, creating, extending, customising and testing the prebuilt informatica mappings and work flows.

Data warehouse Administration Console (DAC) monitors and controls the flow of load of data from source to target. DAC server and client with prebuilt meta data for configuring, monitoring and running the ETL process for specific source containers.

DAC used to schedule the loading of data from source tables to target tables in the source containers.

OBIA Component:

According to Oracle Business Intelligence Applications Installation and Configuration Guide

DAC metadata repository files
This content includes repository objects such as tables, subject areas, execution plans, and tasks, and is contained in XML files.
Embedded Informatica ETL Tool
This is a third-party application that performs the extract, transform, and load operations for the Data Warehouse.
Prebuilt Informatica content
This content includes Extract-Transform-Load (ETL) repository objects, such as mappings, sessions, and work flows, and is contained in the Informatica repository file (Oracle_BI_DW_Base.rep).
Prebuilt metadata content
This meta data content is contained in the Oracle Business Intelligence Applications repository file (OracleBIAnalyticsApps.rpd).
Prebuilt reports and dashboard content
This content is contained in the Oracle BI Presentation Services Catalog.
Oracle Business Analytics Warehouse
The prebuilt data warehouse that holds data extracted, transformed, and loaded from the transactional database.

Some of the Data Sources:

Oracle EBS

People soft

Siebel Source system

JD Edwards


ETL Overview

ETL consists of three components in OBIA Extract, transform—Staging, Load process.

Extracting data from source system and creating staging area for each and every module of applications.

Extracts and consolidates data from one or more source systems and loads into the data warehouse staging tables.

Transforms data in the staging tables and computes calculated values in preparation for the load.

Generates and maintains data warehouse surrogate keys and loads target dimension and fact tables.

Some of the modules like financial, human resource, Supply Chain, procurement, sales, Inventory, Marketing. Etc

Loading of data from source of staging to target tables are in three modes,

Batch ETL (Full or incremental)

Micro ETL

Direct Access to source data from Oracle Bi server

Data Extraction and Load Process:

Source Dependent Extract (SDE) mappings – extracts the data from the transactional systems and loads to the data warehouse staging tables. SDE mappings are designed with respect to the source’s unique data model.

Source specific data will get convert to target tables

While on load of bulk mode if it is interrupted it won’t start at the middle of run, it will get restart of the loading.

While on Normal mode it will get restart even the load is interrupted.

Normal load writes one record at a time.


Source Independent Load (SIL) mappings – extracts and transforms data from the staging tables and loads to the data warehouse target tables. SIL mappings are designed to be universal with any source

Solve foreign key for the dimension tables.

Slowly Changing Dimension 2 concept will carry out if a new record created.

Look up at currency exchange

Generating surrogate key

Defines insert, update, reject while updating rows in source table to target table

Load data as bulk mode.


Post Load Processing (PLP) mapping, which is used to load aggregate tables after target tables have been loaded. This mapping is designed to be source independent.

DAC (Data Warehouse Administration Console)

In data ware house it creates the physical data model, sets the language, currency, time and other settings.

Designing the subject areas to implement, build and run execution plans.

ETL plans will be generated and executed to load the data from source to target.

Error monitoring will carry out during the execution of plans, generates the mail (email Alerts) over the run of plan when errors come.

Structured ETL analysis and reporting will be performed.

Full and incremental load will perform according to the optimisation rule by automated.

Resets from the failure of execution.

Data Model

In general Data Model defines the relation or communication between the client business requirements and technical people.

In terms of data ware house data model – managing large quantity of data as structured and unstructured data model.

Some of the data models are sales, service, marketing, Distribution, finance, human resource operations, workforce and procurement.

In data ware house it creates the physical data model, sets the language, currency, time and other settings.

Tracking historical changes of data from multiple data sources.

Data Models classified into 3 types of model

· Conceptual Model

· Logical Model

· Physical Model

Oracle BI server - Repository

Importing Data sources to physical layer in the Admin tool and making joins for the tables.

Creating logical models in the BMM layer and building measure columns.

Mapping the tables and columns from physical layer to BMM layer and Presentation layer.

Creating different subject areas from BMM layer, creating Hierarchy’s in BMM layer.

Calculated metrics across multiple facts. Creating aggregate navigation. 

Creating Time series metrics like ago function, to date function, snapshot at any point of time

Security implementation for the subject areas.

Physical Layer Importing joins, creating Alias.

BMM layerCreating logical columns, measure columns, aggregate navigation, hierarchy

Presentation LayerSubject areas, Security

Presentation Catalog/Dashboards

Dashboards, reports, analysis are created in the BI answer side using the subject areas created in Admin tool.

Navigation - Drill Down, Drills to detailed level of the report (in Analysis, graph)

Guided NavigationConditional format navigation links, work flows.

Action Links –provides a good feature to show the links in drop down. This option can come into picture when we are navigating to a separate report/page/web pages etc.

This reduces the dashboard complexity by displaying more links on the page and consuming the space in the page. We can open the new analysis in the same window or to a new window.

Alerts / Agents / iBots – scheduling the dashboards, analysis to particular email or user.

Security – Dashboard level of accessing the reports and dashboards using security privileges

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