Oracle Business Intelligence and Data Warehousing Practice Notes and Knowledge Repository

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    This is Santosh Kumar Gidadmani, a Business Intelligence and Data Warehouse Enthusiast passionate about blogging articles in the BI, Data warehousing, space. This is my attempt to share my experience and knowledge on Oracle BI & Data Warehousing Subjects.

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Archive for the ‘DW Components’ Category

Data Warehousing – Components

Posted by Santosh Kumar Gidadmani on January 3, 2011

Data Warehousing Components
We have seen the different data warehousing architectures in the previous series, now let us explore the components of Data warehousing Architecture.

Operational Source Systems
These are the operational systems of record that captures the transactions of the business. All the source systems like, Oracle, SQL Server, DB2 etc are the source systems.

Data Staging Area
The staging area is simply a temporary workspace used to transform and enrich data before it flows into the operational data store (ODS) and the data warehouse. The purpose of staging area is to validate the data through data profiling, data cleansing, data matching and data transformation.

Operational Data Store (ODS)
Since there’s no single universal definition for the ODS, if and where it belongs depend on your situation. ODSs are frequently updated, somewhat integrated copies of operational data. The frequency of update and degree of integration of an ODS vary based on the specific requirement. An ODS is designed for relatively simple queries on small amounts of data (such as finding the status of a customer order), rather than the complex queries on large amounts of data typical of the data warehouse.

ETL Process
Raw data is extracted from the operational source systems and is being transformed into staging area for data cleansing and other formatting, then the data is loaded to ODS for operational reporting and to data warehouse for analytical reporting.

Dimensional Model
Dimensional Modeling is a process to build the data warehouse as per the business requirements. The process involves data analysis of a single business process is performed to identify the fact table granularity, associated dimensions and attributes, and numeric facts. Primary constructs of a dimensional model are fact tables and dimension tables.

Data warehouse
Data warehouse is a single organizational repository of enterprise wide data across many or all subject areas. Data warehouse is an enterprise wide collection of data marts. We have seen many definitions of data ware house in the previous posts.

Data Mart
A data mart is a collection of subject areas organized for decision support based on the needs of a given function.

Business Intelligence Tools
Business Intelligence” refers to reporting and analysis of data stored in the warehouse. Data warehouse is the foundation for business intelligence. Data warehouse/business intelligence (DW/BI) refers to the complete end-to-end system. BI Applications that query, analyze, and present information from the dimensional model. BI applications deliver business value from the DW/BI solution, rather than just delivering the data.

Source Reference: The Data Warehouse Toolkit by Ralph Kimball.

– Santosh

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