Transcript Concepts

Chapter 9
Database Development and Management
Introduction to Information Systems
Judith C. Simon
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Chapter 9 Major Topics
General concepts
File organization
File access
Data models
Distributed databases
Data warehouses and data mining
Knowledge management
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General Concepts
Metadata: data about data, such as descriptions
and relationships
Database: designed to be shared by many people,
although the on-screen data and reports may be
entirely different for each individual need
Entity: each person, place, or thing that is a basis
for maintaining data
Attribute: individual characteristics about an
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File Organization
Refers to the way data is stored, i.e., the relationship
between a record and its location in a file
Address: actual storage location for a record; two
physical, e.g., cylinder, track and sector used on a disk
relative, e.g., record’s position in a file in relation to the
beginning of the file; can be used to create a linked list
(“pointers”), with each record pointing to the next related
record by including its relative address
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File Organization, continued
Types of file organization include:
Sequential: records stored in a specific order,
such as alphabetically, by date, by order number,
Indexed sequential: records divided into groups
and then arranged sequentially within each group
Random ( or “direct”): records stored in any
order, with physical location not a concern for
location records later
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File Access
Concerned with retrieving of files; two options are:
Direct (or “random”): requires that one or more
fields be used as a “key,” or unique identifier for a
record; example: social security number or customer
account number, where no two records would have the
same number
Sequential: files are presented in order from the first
or current record to the last in the designated order
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Data Models
Refers to designing a database by using related models,
starting with a high-level model of some activity,
followed by more detailed models, eventually leading to
a model identifying details of implementation
Conceptual data model: depicts needs from system
users’ viewpoints
Logical data model: based on conceptual model and
includes description of items that need to work together
and other related details; often used for communications
between developers and users
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Examples of Logical Data Models
Hierarchical: top-down (“tree”) structure; main
element is at the top, branching down from there;
efficient but somewhat inflexible structure for data
flow (hierarchical is a one-to-many relationship)
Network: has multiple paths for data flow; more
complicated to design and manage but reduces
unnecessary redundancy (network is a many-tomany relationship)
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Examples of Logical Data Models, continued
Relational: relations are shown as two-dimensional
tables, with attributes used as columns (fields); linking
to another table can occur by having one column of
data that is the same in both; most widely used model
Object-oriented: reusable system that includes
class: person, place, or thing of interest
object: instance of a class, containing related data and
inheritance: new classes can use characteristics of existing
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Database Management Systems
Refers to a complex set of programs for managing
Management tasks include
controlling access to data
coordinating the shared use of data
maintaining quality or integrity of data
managing input/output operations to ensure that they
are as efficient as possible
monitoring system performance
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Distributed Databases
Uses multiple desktop and other computers to spread
the databases over different geographic areas in a
General designs include
placing parts of a database in the locations where they are
most needed
copying (replicating) the entire database at one or more
separate locations
Entire system will not be shut down from a single
power failure, but development and management are
more complex
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Data Warehouse
Typically uses a centralized data storage system
Used for long-range decisions rather than realtime or online decisions
Contains recent as well as historical data but does
not contain up-to-the-minute data that is
constantly changing
Contains integrated data from multiple business
activities, typically arranged by subject
Houses both detailed and summary data
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Data Mining
Involves accessing a data warehouse to examine
data, often to locate patterns and relationships
among items that might not otherwise be noticed,
as well as other influences in a set of data
Often involves neural network techniques that can
adjust as new examples are encountered,
combined with decision support tools
Widely used for marketing activities, sometimes to
predict customer behaviors
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Knowledge Management
Refers to systems that include storage of
knowledge of various employees that can then be
shared with others (their knowledge includes such
things as methods they have used for successful
handling of situations and other procedures that
are not otherwise found in programs or databases)
Often used to assist in business decisions or to
improve customer service
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