Dataware House Architecture

1947 Words Jun 25th, 2015 8 Pages
DATA WAREHOUSE ARCHITECTURE

Albina Yusupova
Data Warehouse Architecture

The main difference between the database architecture in a standard, on-line transaction processing oriented system (usually ERP or CRM system) and a Data Warehouse is that the system’s relational model is usually de-normalized into dimension and fact tables which are typical to a data warehouse database design. The differences in the database architectures are caused by different purposes of their existence.
In a typical OLTP system the database performance is crucial, as end-user interface responsiveness is one of the most important factors determining usefulness of the application. That kind of a database needs to
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In view of this, it is far more reasonable to present the different layers of a data warehouse architecture rather than discussing the specifics of any one system.

In general, all data warehouse systems have the following layers:

Data Source Layer
Data Extraction Layer
Staging Area
ETL Layer
Data Storage Layer
Data Logic Layer
Data Presentation Layer
Metadata Layer
System Operations Layer

The picture below shows the relationships among the different components of the data warehouse architecture:
Metadata Layer

Data Source Layer Data Extraction Layer Staging Area ETL Layer Data Storage Layer Data Logic Layer Data Presentation Layer System Operations Layer

Each component is discussed individually below:

Data Source Layer
This represents the different data sources that feed data into the data warehouse. The data source can be of any format - plain text file, relational database, other types of database, Excel file, etc., can all act as a data source.
Many different types of data can be a data source:
· Operations - such as sales data, HR data, product data, inventory data, marketing data, systems data.
· Web server logs with user browsing data.
· Internal market research data.
· Third-party data, such as census data, demographics data, or survey data.

All these data sources together form the Data Source Layer.
Data Extraction Layer
Data gets pulled from the
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