Database Systems: Data and Information

Learning Objectives

• The chapter covers the difference between data and information
• This chapter discusses what a database is as well as the various types of databases
• This chapter covers why databases are valuable assets for decision making
• The chapter will discuss the importance of database design
• How modern databases evolved from file systems will be covered
• Flaws in file system data management
• Explains the main components of a database system
• Explains the primary functions of a database management system (DBMS)

Data vs Information

• Data consists of raw facts
• Raw data has not been processed to reveal its meaning
• Data represents the building blocks of information
• Data management: generation, storage, and retrieval of data
• Information is produced by processing data
• Information reveals the meaning of data
• Information enables knowledge creation
• Information should be accurate, relevant, and timely for good decision making

Database Components

• Databases store a shared, integrated computer structure
• End-user data refers to raw facts of interest to the end-user
• Metadata is data about data; it integrates and manages end-user data
• Metadata describes data characteristics and relationships
• A database management system (DBMS) manages databases
• DBMS is a collection of programs
• A DBMS manages the database structure, controls access to data stored in the database

The Role of DBMS

• The DBMS is an intermediary between the user and the database
• DBMS enables data to be shared
• DBMS presents the end user with an integrated view of the data
• DBMS receives and translates application requests into operations required to fulfill requests
• DBMS hides database's internal complexity from the application programs and users

Advantages of a DBMS

• Better data integration and less inconsistency
• Data inconsistency: different versions of the same data appear in different places
• Improved end-user productivity
• Data sharing improves
• Data security improves
• Data access improves
• Decision making improves
• Data quality promotes accuracy, validity, and the timeliness of data

Types of Databases

• Single-user database: supports one user at a time
  • Desktop database: runs on a PC
• Multiuser database: supports multiple users at the same time
  • Workgroup database: supports a small number of users or specific department
  • Enterprise database: supports many users across many departments
• Centralized database: data located at a single site.
• Distributed database: data distributed across different sites
• Cloud database: created and maintained using cloud data services with defined performance measures
• General-purpose databases: Contains a wide variety of data used in multiple disciplines
• Discipline-specific databases: Contains data focused on specific subject areas
• Operational database: Designed to support a company's day-to-day operations
• Analytical database: Stores historical data and business metrics used exclusively for tactical or strategic decision making
  • Data warehouse: Stores data in a format optimized for decision support
• Online analytical processing (OLAP): enables retrieving, processing, and modeling data from the data warehouse
• Business intelligence: captures and processes business data to generate information that supports decision-making
• Unstructured data: Exists in its original state
• Structured data: results from formatting, with the structure applied based on the type of processing to be performed
• Semistructured data: Processed to some extent
• Extensible Markup Language (XML): represents data elements in textual format

Database Designs

• Focuses on the design of the database structure used to store and manage end-user data
• Well-designed database facilitates data management and generates accurate, valuable information
• Poorly designed databases cause difficult-to-trace errors

Evolution of File System Data Processing

• Manual File Systems were accomplished through a system of file folders and filing cabinets
• Computerized File Systems were created by Data processing (DP) specialists to create computer-based systems to track data and produce reports
• File System Redux: Modern End-User Productivity Tools such as Microsoft Excel

Basic File Terminology

• Data: Raw facts, such as a telephone number, a birth date, a customer name, and a year-to-date sales value
  • Data has little meaning unless organized
• Field: A character, or group of characters, that has a specific meaning
  • It is used to define and store data
• Record: A logically connected set of one or more fields that describes a person, place, or thing
• File: A collection of related records

Problems with File System Data Processing

• Lengthy development times
• Difficulty of getting quick answers
• Complex system administration
• Lack of security and limited data sharing
• Extensive programming

Structural and Data Dependence

• Structural dependence: Access to a file depends on its structure
  • Therefore all file system programs must be modified to conform to a new file structure
• Structural independence: File structure changes without affecting the application's ability to access the data
• Data dependence: Data access changes when data storage characteristics change
• Data independence: Data storage characteristics change without affecting the program's ability to access the data
• Practical significance of data dependence is the difference between the logical and physical format

Redundancy

• Unnecessarily storing the same data at different places
• Islands of information have scattered data locations
  • Increases the probability of having different versions of the same data

Redundancy Implications

• Poor data security
• Data inconsistency
• There is an increased likelihood of data-entry errors when complex entries are made in different files
• Data anomaly: Develops when not all required changes in redundant data are made successfully
  • Update anomalies
  • Insertion anomalies
  • Deletion anomalies

Lack of Design and Data-Modeling Skills

• Evident despite the availability of multiple personal productivity tools
• Data-modeling skills are a vital part of the data design process
• Good data modeling facilitates communication between the designer, user, and the developer

Database Systems

• Logically related data is stored in a single logical data repository
  • Can be physically distributed among multiple storage facilities
• DBMS eliminates most file system problems
• Current generation DBMS software stores data structures, relationships between structures, and access paths
• Current generation DBMS software defines, stores, and manages all access paths and components

DBMS Functions

• The Data dictionary stores definitions of data elements and their relationships
• Performance tuning: Ensures efficient database performance in terms of storage and access speed
• Data transformation transforms entered data to conform to the required data structures
• Security Management enforces user security and data privacy
• Sophisticated algorithms ensure multiple users can access the database concurrently without compromising integrity using access control
• Enables database recovery after a failure with backup and recovery management
• Minimizes redundancy and maximizes consistency with data integrity management
• Query languages let the users specify what must be done to specify how using access languages and application programming interfaces
• Structured Query Language (SQL): a de facto query and data access standard supported by most DBMS vendors
• End-user database requests are accepted via different network environments

Disadvantages of Database Systems

• Increased costs
• Management complexity
• Maintaining currency
• Vendor dependence
• Frequent upgrade/replacement cycles