The
term "Data Warehouse" was first coined by Bill Inmon in 1990. He said
that Data warehouse is subject Oriented, Integrated, Time-Variant and
nonvolatile collection of data.This data helps in supporting decision making
process by analyst in an organization The operational database undergoes the
per day transactions which causes the frequent changes to the data on daily
basis.But if in future the business executive wants to analyse the previous
feedback on any data such as product,supplier,or the consumer data. In this
case the analyst will be having no data available to analyse because the
previous data is updated due to transactions. The Data Warehouses provide us
generalized and consolidated data in multidimensional view. Along with
generalize and consolidated view of data the Data Warehouses also provide us
Online Analytical Processing (OLAP) tools. These tools help us in interactive
and effective analysis of data in multidimensional space. This analysis results
in data generalization and data mining. The data mining functions like
association,clustering ,classification, prediction can be integrated with OLAP
operations to enhance interactive mining of knowledge at multiple level of
abstraction. That's why data warehouse has now become important platform for
data analysis and online analytical processing.
Understanding Data Warehouse
The Data Warehouse is that
database which is kept separate from the organization's operational database.
There is no frequent updation
done in data warehouse.
Data warehouse possess
consolidated historical data which help the organization to analyse it's
business.
Data
warehouse helps the executives to organize, understand and use their data to
take strategic decision.
Data warehouse systems available which
helps in integration of diversity of application systems.
The Data warehouse system
allows analysis of consolidated historical data analysis.
Definition
Data warehouse is Subject
Oriented, Integrated, Time-Variant and Nonvolatile collection of data that
support management's decision making process.
Why Data Warehouse Separated from Operational Databases
The following are the
reasons why Data Warehouse are kept separate from operational databases:
The operational database is constructed
for well known tasks and workload such as searching particular records,
indexing etc but the data warehouse queries are often complex and it presents
the general form of data.
Operational databases support the
concurrent processing of multiple transactions.Concurrency control and recovery
mechanisms are required for operational databases to ensure robustness and
consistency of database.
Operational database query allow
reading, modifying operations while the OLAP query need read only access
of stored data.
Operational database
maintain the current data on the other hand data warehouse maintain the
historical data.
Data
Warehouse Features
The key features of Data Warehouse such as Subject Oriented,
Integrated, Nonvolatile and Time-Variant are are discussed below:
Subject Oriented - The Data
Warehouse is Subject Oriented because it provides us the information around a
subject rather the organization's ongoing operations. These subjects can be
product, customers, suppliers, sales, revenue etc. The data warehouse does not
focus on the ongoing operations Rather it focuses on modelling and analysis of
data for decision making.
Integrated - Data Warehouse is
constructed by integration of data from heterogeneous sources such as
relational databases, flat files etc. This integration enhances the effective
analysis of data.
Time-Variant - The Data in Data
Warehouse is identified with a particular time period. The data in data
warehouse provide information from historical point of view
Non Volatile - Non volatile means
that the previous data is not removed when new data is added to it. The data
warehouse is kept separate from the operational database therefore frequent
changes in operational database are not reflected in data warehouse.
Note: - Data Warehouse does not
require transaction processing, recovery and concurrency control because it is
physically stored separate from the operational database.
Data
Warehouse Applications
As discussed before Data Warehouse helps the business executives
in organize, analyse and use their data for decision making. Data Warehouse
serves as a soul part of a plan-execute-assess "closed-loop" feedback
system for enterprise management. Data Warehouse is widely used in the
following fields:
financial services
Banking Services
Consumer goods
Retail sectors.
Controlled manufacturing
