Simon Text Book

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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
  entity

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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 types
• physical, e.g., cylinder, track and sector used
  on a disk
• relative, e.g., records 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,
  etc.
• 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-to-many
  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 methods
• inheritance new classes can use characteristics
  of existing classes

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Database Management Systems

• Refers to a complex set of programs for managing
  databases
• 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 network
• 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
  real-time 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