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Vidyalankar
T.Y. B.Sc. (IT) : Sem. VI
Data Warehousing
Prelim Question Paper Solution

Data Warehouse
Creating data to be analytical requires that it be subject-oriented, integrated,
time-referenced, and non-volatile.
Subject-Oriented Data
In a data warehouse environment, information used for analysis is organized
around subjectsemployees, accounts, sales, products, and so on. This subject
specific design helps in reducing the query response time by searching through
very few records to get an answer to the user’s question.
Integrated Data
Integrated data refers to de-duplicating information and merging it from many
sources into one consistent location. When short listing your top 20 customers,
you must know that “HAL” and “Hindustan Aeronautics Limited” are one and the
same. There must be just one customer number for any form of HAL or
Hindustan Aeronautics Limited, in your database.
Time-Referenced Data
The most important and most scrutinized characteristic of the analytical data is its
prior state of being. In order words, time-referenced data essentially refers to its
time-valued characteristic. For example, the user may ask “What were the total
sales of product ‘A’ for the past three years on New Year’s Day across region
‘Y’?” To answer this question, you need to know the sales figures of the product
on New Year’s Day in all the branches for that particular region.

Source System
Operational systems process data to support critical operational needs. In order
to do this, operational databases have been historically created to provide an
efficient processing structure for a relatively small number of well-defined
business transactions. However, because of the limited focus of operational
systems, the databases designed to support operational systems have difficulty
accessing the data for other management or informational purposes. This
difficulty is amplified by the fact that many operational systems are often 10-15
years old. This in turn means that the data access technology available to obtain
operational data is itself dated.
Source Data Transport Layer
The data transport layer of the DWA, largely constitutes data trafficking. It
particularly represents the tools and processes involved in transporting data from
the source systems to the enterprise warehouse system.