Data warehouses and their architectures vary depending upon the situation:-
Data warehouses often adopt a three – tier architecture,
1 Bottom tier
2 Middle tier
3 Top tier
Data Warehouse Architecture
The bottom tier of the architecture is the data warehouse database server.It is the relational database system. Data is feed into bottom tier by some back-end tools and utilities.
1 Data Extraction
2 Data Cleaning
3 Data Transformation
4 Load
5 Refresh
The middle tier is an OLAP server present user a multidimensional data from data warehouse.Middle tier is an OLAP server can be implemented using either relational OLAP (ROLAP) model or multidimensional OLAP (MOLAP) model.
ROLAP is an extended relational database management system. The ROLAP maps the operations on multidimensional data to standard relational operations.
MOLAP directly implements multidimensional data and operations.
The top tier is a front-end client layer.
Query and Reporting tools - Production reporting tool.
Analysis tools - Prepare charts based on analysis.
Data mining tools - Discover hidden knowledge, pattern.
Data warehouse provide critical information to business analyst to measure performance of business and help in the process of decision-making.With data warehouse business productivity can be enhance because business analyst can quickly gather information that describes the organization.
Data warehouse provide customers view which help to improve customer relationship.Data warehouse can also help in cost reduction by tracking trends and patterns.
Top-down view allow the selection of the relevant information necessary for the data warehouse.
Data source view presents information being captured, stored, and managed by operational systems.This information may be documented at various levels of detail and accuracy, from individual data source tables to integrated data source tables.
Data warehouse view includes fact tables and dimension tables.This view represents the information that is stored inside the data warehouse.
Business query view is view of data in the data warehouse from the viewpoint of the end user.
Differences between Operational Database Systems and Data Warehouses
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