Decision-support systems are designed to allow analysts to extract
information quickly and easily. The data being analyzed is often historical:
daily, weekly, and yearly results. Examples of decision-support systems include
applications for analysis of sales revenue, marketing information, insurance
claims, and catalog sales. A decision-support database within a single business
can include data from beginning to end: from receipt of raw material at the
manufacturing site, entering orders, tracking invoices, and monitoring database
inventory to final consumer purchase. These systems are used to manage a
business. They provide the information needed for business analysis and
planning.
Decision-support systems have the following characteristics:
·
Understandability
Data structures must be readily understood by
users, often requiring denormalization and precomputed aggregations (summary
data).
·
Relatively infrequent
changes
Most changes to the database occur in a controlled
manner when data is loaded at regular intervals.
·
Join paths
Join paths are simple, noncyclical, and based on
business relations. They are defined when the database is built.
·
Relational integrity
Relational integrity, necessary to ensure
correct results, is built into the database when the data is loaded or deleted.
·
Unpredictable and
complex SQL queries
SQL query statements submitted against the
database vary considerably and unpredictably from query to query. They can
contain long, complex SELECT statements that make comparisons or require
sequential processing. These queries might reference many thousands, millions,
or even billions of records in a database.
·
Large result sets
Extensive and frequent browsing must be
supported.
·
Recoverability
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