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What is Data Warehousing?
About Data Warehousing
A data warehouse is a database of data gathered from many systems and intended to
support management reporting and decision making.
Goals of data warehousing
(1) To provide a reliable, single, integrated source of key corporate information.
(2) To give end users access to their data without a reliance on reports produced
by the IS department.
(3) To allow analysts to analyze corporate data and even produce predictive “what-if”
models from that data.
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About Business Intelligence
Data warehousing provides business intelligence. A business intelligence system
is a system that gives users access to their data and allows them to analyze and
format the data as needed.
Data Warehouse Defined
The data warehouse is a subject-oriented, integrated, nonvolatile, time-variant
collection of data in support of management decisions.
In user-friendly terms, a data warehouse is a collection of snapshots of data taken
from transaction processing systems at given intervals. Data warehouses are databases
used solely for reporting.
About Online Transaction Processing - OLTP Databases
OLTP databases hold information about small subsets of the organization. For example,
a retailer may have separate order-entry systems and databases for retail, catalog
and outlet sales. But suppose you want to run a query on all sales, not simply the
sales captured by a particular system. To address this kind of situation your data
warehouse should be subject-oriented: organized around subject areas, like sales,
rather than around OLTP data sources. The data from separate systems can be accessed
from one place and queried on one report.
To create a useful subject area, the source data sources must be integrated in the
data warehouse. This means that the data warehouse is read only; users can’t write
back. Unlike operational databases, warehouses primarily support reporting, not
data capture.
Without a time component, most information is meaningless. To say, sales were $5,000,000
isn’t useful because it doesn’t indicate the time period during which sales equaled
$5,000,000. Also most business reporting requires the analysis of trends. Trend
analysis requires access to historical data. Most operational systems don’t store
a large amount of history so as not to impact response time. Warehouses on the other
hand, hold large amounts of history. This is one of the main reasons why warehouses
are often huge databases.
How does Business Intelligence differ from Transaction Processing in Operational
systems? - Data Warehousing
Operational systems are designed to work with small pieces of information, unlike
data warehouses.
Operational data must frequently be updated in real time, unlike data warehouses.
Operational system schemas are designed for rapid data input, unlike data warehouses.
Operational users need immediate response, unlike data warehouses.
Operational system usage patterns are relatively predictable, unlike data warehouses.
The database design of operational systems tends to be very complex, unlike data
warehouses.
If you want more information about data warehousing, use the Data Warehouse Search
Engine below:
(Returns specially relevant / customised results for Data Warehouse)
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