Data Warehouse Architecture - Evolving Application Domains of Data Warehousing and Mining - page 15

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Data Warehouse: Data warehouse is a reposi-
tory of an organization's data. Data warehouses
provide data for business intelligence applications
such as reporting and analysis, dash board, bal-
anced scorecard, etc.
ETL: Extract, transform, and load (ETL)
describes a data warehouse process where data
from various source locations are transformed
through a data integration process into the target
locations. Extract is a process of extracting data
from outside sources. Transform is a process of
transforming data to fit the operational require-
ment. Load is a process of loading the data to the
end target.
Master Data Management: Master data
management (MDM) is a data management dis-
cipline to actively manage master data throughout
an organization. Master data represents the most
correct non-transaction information of an enter-
prise, such as customer, product, and organization
information.
System Architecture: System architecture is
the design of structure and behavior of a system.
Normally system architecture is represented in a
conceptual diagram where different components
and their connections are described.
Service-Oriented Architecture: Service-
oriented architecture is a system architecture
pattern that defines methods for development
and integration of systems. In a service-oriented
architecture, all functionalities of all the systems
are designed in favor of the various business
processes that these systems support. These
functionalities, also termed as services, are then
packaged for reuse.

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key terMS And defInItIonS

Data Integration: Data integration is a process
of transforming data at different sources into data
at one or more target locations.
Data Mart: Data mart is a data silo of an
organization's data. A data mart normally stores
data that is oriented to a specific purpose or of a
major data subject that is used for specific busi-
ness needs.