it for business
jaggat
hc1041_week_08.pptx
Chapter 7
Organising Data and Information
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Principles
The database approach to data management provides significant advantages over the traditional file-based approach.
A well-designed and well-managed database is an extremely valuable tool in supporting decision making.
The number and types of database applications will continue to evolve and yield real business benefits.
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Learning Objectives
LO1: Define general data management concepts and terms, highlighting the advantages of the database approach to data management.
LO2: Describe the relational database model and outline its basic features.
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Learning Objectives
LO3: Identify the common functions performed by all database management systems and identify popular end-user database management systems.
LO4: Identify and briefly discuss current database applications.
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Data Management
Data consists of raw facts, such as employee numbers or sales figures.
For data to become useful information, it must first be organised in a meaningful way.
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The Hierarchy of Data
A bit (a binary digit) represents a circuit that is either on or off.
Bits are organised into units called bytes.
A byte is typically 8 bits.
Character: Each byte represents a character, the basic building block of information.
Field: Typically a name, number, or combination of characters that describes an aspect of a business object or activity.
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The Hierarchy of Data
Record: A collection of related data fields.
File: A collection of related records.
Database: A collection of integrated and related files.
Hierarchy of data: Formed by bits, characters, fields, records, files, and databases.
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Data Entities, Attributes, and Keys
Entity: A generalised class of people, places, or things (objects) for which data is collected, stored, and maintained.
Attribute: A characteristic of an entity.
Data item: The specific value of an attribute.
Key: A field or set of fields in a record that is used to identify the record.
Primary key: A field or set of fields that uniquely identifies the record.
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The Traditional Approach
Traditional approach: Separate data files are created and stored for each application program.
Results in data redundancy: duplication of data in separate files
Data redundancy conflicts with data integrity (the degree to which the data in any one file is accurate)
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The Database Approach
Database approach: Approach whereby a pool of related data is shared by multiple application programs; offers significant advantages over traditional file-based approach.
Controls data redundancy
More efficient with increased data integrity
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Advantages of the Database Approach
Improved strategic use of corporate data
Reduced data redundancy
Improved data integrity
Easier modification and upgrading
Data and program independence
Better access to data and information
Standardisation of data access
A framework for program development
Better overall protection of the data
Shared data and information resources
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Disadvantages of the Database Approach
More complexity
More difficult to recover from a failure
More expensive
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Data Modelling and the Relational Database Model
When building a database, an organisation must consider:
Content: What data should be collected and at what cost?
Access: What data should be provided to which users and when?
Logical structure: How should data be arranged so that it makes sense to a given user?
Physical organisation: Where should data be physically located?
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Data Modelling
Building a database requires two types of designs:
Logical design: Shows an abstract model of how the data should be structured and arranged to meet an organisation’s information needs
Physical design: Starts from the logical database design and fine-tunes it for performance and cost considerations
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Data Modelling
Data model: A diagram of data entities and their relationships.
Entity-relationship (ER) diagrams: Data models that use basic graphical symbols to show the organisation of and relationships between data.
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The Relational Database Model
Relational model: Describes data in which all data elements are placed in two-dimensional tables, called relations, that are the logical equivalent of files.
In the relational model:
Each row of a table represents a data entity
Columns of the table represent attributes
Domain: The allowable values for data attributes.
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Manipulating Data
Selecting: Eliminates rows according to certain criteria.
Projecting: Eliminates columns in a table.
Joining: Combines two or more tables.
Linking: Combines two or more tables using common data attributes to form a new table with only the unique data attributes.
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Database Management Systems (DBMS)
A group of programs used as an interface between a database and application programs or a database and user.
Database types:
Flat file
Single user
Multiple users
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Database Management Systems (DBMS)
Schema: A description of the entire database.
User view: The portion of the database a user can access. Subschemas are used to create different user views.
Subschema: A file that contains a description of a subset of the database and identifies which users can view and modify the data items in the subset.
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Database Management Systems (DBMS)
Fig 7.10: The Use of Schemas and Subschemas
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Creating and Modifying the Database
Data definition language (DDL):
A collection of instructions and commands used to define and describe data and data relationships in a specific database.
Allows the database’s creator to describe the data and the data relationships that are to be contained in the schema and subschemas.
Data dictionary: A detailed description of all the data used in the database.
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Storing and Retrieving Data
When an application program request data from DBMS, the application program follows a logical access path.
When the DBMS goes to a storage device to retrieve the requested data, it follows a path to the physical location (physical access path) where the data is stored.
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Manipulating Data and Generating Reports
Data manipulation language (DML): The commands that are used to manipulate the data in a database.
Structured Query Language (SQL): Adopted by the American National Standards Institute (ANSI) as the standard query language for relational databases.
Once a database has been set up and loaded with data, it can produce reports, documents, and other outputs.
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Database Administration
Responsibilities include:
Designing, implementing, and maintaining the database system and the DBMS
Establishing policies and procedures regarding management, security, maintenance and usage
Training employees in database management and use
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Popular Database Management Systems
Popular DBMSs for end users include Microsoft’s Access and Corel’s Paradox.
The complete database management software market includes databases by IBM, Oracle, and Microsoft.
Examples of open-source database systems: PostgreSQL and MySQL.
Many traditional database programs are now available on open-source operating systems.
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Special-purpose Database Systems
Used for specific purposes or industries.
Examples:
Summation or Concordance, used in law firms for legal documents
Scottish Intelligence Database, used by Scottish police to share crime reports
GlobalSpec, used for engineers and product designers
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Selecting a Database Management System
Important characteristics of databases to consider:
Size of the database
Number of concurrent users
Performance
The ability of the DBMS to be integrated with other systems
Features of the DBMS
Vendor considerations
Cost of the system
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Using Databases with Other Software
DBMS can act as front-end or back-end application.
Front-end application: Directly interacts with people or users.
Back-end application: Interacts with other programs or applications
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Linking the Company Database to the Internet
Corporate databases can be accessed by customers, suppliers, and company employees through:
The Internet
Intranets
Extranets
Semantic Web: A seamless integration of traditional databases with the Internet
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Data Warehouses, Data Marts, and Data Mining
Data warehouse: A database that collects business information from many sources in the enterprise, covering all aspects of the company’s processes, products, and customers.
Data mart: A subset of a data warehouse.
Data mining: An information-analysis tool that involves the automated discovery of patterns and relationships in a data warehouse.
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Business Intelligence
Business intelligence (BI): The process of gathering enough of the right information in a timely manner and usable form and analysing it to have a positive impact on business strategy, tactics, or operations.
Knowledge management: The process of capturing a company’s collective expertise wherever it resides and distributing it wherever it can help produce the biggest payoff.
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Distributed Databases
Distributed database:
A database in which the data may be spread across several smaller databases connected via telecommunications devices
Corporations get more flexibility in how databases are organised and used
Replicated database: A database that holds a duplicate set of frequently used data.
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Online Analytical Processing (OLAP)
Programs used to store and deliver data warehouse information efficiently.
Supports data analysis and decision making
Top-down, query-driven data analysis
User must be very knowledgeable of the data and its business context
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Object-Oriented and Object-Relational Database Management Systems
Object-oriented database:
Stores both data and its processing instructions
Method: A procedure or action
Message: A request to execute or run a method
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Object-oriented database management system (OODBMS): Group of programs that manipulate an object-oriented database and provide a user interface and connections to other application programs.
Object-relational database management system (ORDBMS): DBMS capable of manipulating audio, video, and graphical data.
Object-Oriented and Object-Relational Database Management Systems
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Visual, Audio, and Other Database Systems
Companies have an increasing need to store large amounts of visual and audio signals.
Credit card companies
Hospitals
Music companies, etc.
Virtual database systems: Allow different databases to work together as a unified database system.
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Summary
Hierarchy of data: Bits, characters, fields, records, files, and databases.
Entity: A generalised class of things (objects) for which data is collected, stored, and maintained.
Attribute: Characteristic of an entity.
Data model: Diagram of entities and relationships.
Relational model: Describes data in which all elements are placed in two-dimensional tables called relations.
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Summary
Selecting: Eliminates rows according to certain criteria.
Projecting: Eliminates columns in a table.
Database management system (DBMS): Group of programs used as an interface.
Between a database and application programs
Between a database and the user
Data dictionary: Detailed description of all the data used in the database.
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Summary
Data warehouse: Database that collects business information from all aspects of a company’s processes, products, and customers.
Data mining: An information-analysis tool for the automated discovery of patterns and relationships in a data warehouse.
Open database connectivity (ODBC) standards: Ensure that software can be used with any ODBC-compliant database.
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