Organizing Data & Information Chapter 5. 2 IS for Management Data & Databases Data consists of raw facts that when organized may be transformed into information

Organizing Data & Information

Chapter 5

Chapter 5 IS for Management2

Data & Databases

Data consists of raw facts that when organized may be transformed into information

A Database is a collection of data organized to meet users’ needs

A Database Management System (DBMS) isa group of programs that manipulate the database &

provide an interface between the database & the user of the database or other application programs


The Hierarchy of Data (Figure 5.1)

Database Management System

Database

File (table)

Record (entity, row)

Field (characteristic, column)

Byte (character)


Data Entities, Attributes, & Keys

Entity: A generalized class of people, places, or things for which data is collected, stored, & maintained

• Examples: customers, employees Attribute: A characteristic of an entity;

something the entity is identified by• Examples: customer name, employee name

Key: A field or set of fields in a record that is a unique identifier of a record

• Examples: social insurance number, customer number


Keys & Attributes (Figure 5.2)<

--------Entities-------->

(records)

EmployeeNumber

Last Name First Name Hire Date DepartmentNumber

005-10-6321 Johns Francine 10-7-65 257

549-77-1001 Buckley Bill 2-17-79 650

098-40-1370 Fiske Steven 1-5-85 598

Key Field

<-------------------------------------Attributes------------------------------------>


The Traditional Approach (Figure 5.3)

Separate files are created & stored for each application program


Drawbacks to the Traditional Approach Data redundancy

– Duplication of data in separate files Lack of data integrity

– The degree to which the data in any one file is accurate Program-data dependence

– A situation in which programs & data organized for one application are incompatible with programs & data organized differently for another application

Inability to Link Data


The Database Approach (Figure 5.4)

A pool of related data is shared by multiple applications. Rather than having separate data files, each application uses a collection of data that is either joined or related in the database.


Advantages to the Database Approach

Improved strategic use of corporate data Reduced data redundancy Improved data integrity Easier modification & updating Data & program independence Better access to data & information Standardization of data access A framework for program development Better overall protection of the data Shared data & information resources


Disadvantages to the Database Approach

Relatively high cost of purchasing & operating a DBMS in a mainframe operating environment

Increased cost of specialized staff Increased vulnerability


Database Design

Logical design precedes physical design– Abstract model of how data should be structured &

arranged– Users should assist in creating logical design

Physical design starts with the logical design– What specific hardware/software will be used– Fine-tuning of logical design for performance/cost

considerations– Planned Data Redundancy

• A way of organizing data in which the logical database design is altered so that certain data entities are combined

– Summary totals are carried in the data records rather than calculated from elemental data

– Some data attributes are repeated in more than one data entity to improve database performance


Data Modeling

Data Model– A map or diagram of entities & their relationships

Enterprise data modeling– Data modeling done at the level of the entire

organization Entity-Relationship (ER) diagrams

– A data model that uses basic graphical symbols to show the organization of & relationships between data (Figure 5.5)


Database Models

Hierarchical (Figure 5.6): A data model in which the data is organized in a top-down or inverted tree structure

Network (Figure 5.7): An expansion of the hierarchical database model with an owner-member relationship in which a member may have many owners

Relational (Figure 5.8): All data elements are placed in two-dimensional tables, called relations, that are the logical equivalent of files


A Relational Database (3 tables)


Relational Database Terminology

Domain: Allowable values for attributes Selecting: Data manipulation that eliminates rows

(records) according to user-defined criteria Projecting: Data manipulation that eliminates

columns (attributes) in a table Joining: Data manipulation that combines two or

more tables Linking: Relating tables in a relational database

together by a common attribute(s)


Schemas & Subschemas

Schema– View of the entire database– Includes logical & physical structure & relationships

among all data

Subschema– User view of a portion of the database– Can have many subschemas for one database


Data Definition Language & Dictionary Data Definition Language (DDL)

– A collection of instructions & commands used to define & describe data & data relationships in a database

Data Dictionary– A detailed description of all data used in the database

• Provides a standard definition of terms & data elements• Assists programmers in designing & writing programs• Simplifies database modification• Reduces data redundancy• Increases data reliability• Faster program development• Easier modification of data & information


Logical & Physical Access Paths (Figure 5.14)

Logical Access Path

Application requires information from the DBMS

Physical Access Path

DBMS accesses a storage device to retrieve data

Data on

Storage

Device

DBMS

Management

inquiries

Other

Software

Application

Programs


Manipulating Data

Concurrency Control– A method of dealing with a situation in which two or

more people need to access the same record in a database at the same time

Data Manipulation Language (DML)– The commands that are used to manipulate the data in a

database Structured Query Language (SQL)

– A standardized data manipulation language for querying a database

– Most modern databases are SQL compliant


DBMS Selection Criteria

Database size Number of concurrent users Performance Integration Features Vendor Cost


Database Developments (1)

Distributed Database– A database in which the actual data may be spread

across several smaller databases connected via telecommunications devices

– Transparent to user (user does not know where data is) Replicated Database

– Duplicate of original database (saves telecom time/$$)



Data Warehouse– A relational database management system designed

specifically to support management decision making Data Mart

– A subset of a data warehouse for small & medium-size businesses or departments within larger companies

Data Mining– Automated discovery of patterns & relationships in a

data warehouse– Built-in analysis tools



On-line Transaction Processing (OLTP)– TP happens at time of transaction

On-line Analytical Processing (OLAP)– Supports high speed analysis of data involving complex

relationships Multidimensional Databases

– Data can include graphics, photographs, sound files, etc.

Open Database Connectivity (ODBC)– Software written in compliance with ODBC standards

can be used with any ODBC-compliant database


Object-Relational Database Management Systems

Can manipulate audio, video, & graphical data

Hypertext: Users can search & manipulate alphanumeric data in an unstructured way

Hypermedia: Users can search & manipulate multimedia forms of data

Spatial Data Technology: Use of an object-relational database to store & access data according to the location it describes & to permit spatial queries & analysis


Case

US West

Documents

Organizing Data & Information Chapter 5. 2 IS for Management Data & Databases Data consists of raw facts that when organized may be transformed into information