Database Systems Notes

Data vs. Information

• Data: Raw facts that have not yet been processed to reveal their meaning.
  • Considered the building blocks of information.
• Information: The result of processing raw data to reveal its meaning.
  • Requires context to be meaningful.
  • Forms the bedrock of knowledge, and should be accurate, relevant, and timely.

Introducing the Database

• A shared, integrated computer structure that stores data.
• Consists of:
  • End-user data: Raw facts of interest to the end-user.
  • Metadata: Data about data which provides description of data characteristics and relationships.
• Utilizes a Database Management System (DBMS) that is a collection of programs to manage the database structure and control access to the data.

Role and Advantages of the DBMS

• The DBMS acts as an intermediary between the user and the database.
• Enables data sharing by presenting an integrated view of the data to the end-user.
• Offers more efficient and effective data management.
• Improves sharing, security, integration, access, decision-making capabilities and overall productivity.

Types of Databases

• Classification by number of users:
  • Single-user database: Supports one user at a time; a desktop database falls under this category.
  • Multiuser database: Supports multiple users simultaneously; categorized into workgroup (small number of users) and enterprise (many users across many departments) databases.
• Classification by location:
  • Centralized database: Data is located at a single site.
  • Distributed database: Data is distributed across different sites.
  • Cloud database: Created and maintained using cloud data services with defined performance measures.
• Classification by data type:
  • General-purpose database: Contains a wide variety of data used in multiple disciplines.
  • Discipline-specific database: Contains data focused on specific subject areas.
  • Operational database: Supports a company’s day-to-day operations.
  • Analytical database: Stores historical data and business metrics used for tactical or strategic decision-making.
    • Data warehouse: Stores data optimized for decision support.
    • Online analytical processing (OLAP): Tools for retrieving, processing, and modeling data from the data warehouse.
    • Business intelligence: Captures and processes business data to generate information that supports decision-making.
• Classification by degree of structure:
  • Unstructured data: Exists in its original (raw) state.
  • Structured data: Results from formatting, with structure applied based on the type of processing to be performed.
  • Semistructured data: Processed to some extent, often using Extensible Markup Language (XML) to represent data elements in textual format.

Why Database Design Is Important

• Database design focuses on the structure that will be used to store and manage end-user data.
• A well-designed database facilitates efficient data management and generates accurate, valuable information.
• A poorly designed database can lead to errors that are difficult to trace, potentially resulting in poor decision-making.

Evolution of File System Data Processing

• Manual file systems: Accomplished through a system of file folders and filing cabinets.
• Computerized file systems: Data processing (DP) specialists created computer-based systems to track data and produce required reports.
• File system redux: modern end-user productivity tools, including spreadsheet programs like Microsoft Excel.

Basic File Terminology

Problems with File System Data Processing

• Problems include:
  • Lengthy development times
  • Difficulty obtaining quick answers
  • Complex system administration
  • Lack of security and limited data sharing
  • Extensive programming requirements

Structural and Data Dependence

• Structural dependence: Access to a file is dependent on its structure; file system programs must be modified to conform to new file structures.
• Structural independence: File structure can be changed 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 can be changed without affecting the program’s ability to access the data.
  • The practical significance of data dependence is the difference between logical and physical format.

Data Redundancy

• Unnecessarily storing the same data in different places, leading to scattered data locations (islands of information).
• Increases the probability of having inconsistent versions of the same data.
• Possible results of uncontrolled data redundancy include:
  • Poor data security
  • Data inconsistency
  • Data-entry errors
  • Data integrity problems

Data Anomalies

• Develop when not all of the required changes in the redundant data are made successfully
• Types of anomalies:
  • Update anomalies
  • Insertion anomalies
  • Deletion anomalies

Database Systems

• Logically related data stored in a single logical data repository but physically distributed among multiple storage facilities.
• DBMS eliminates most of the file system's data inconsistency, data anomaly, data dependence, and structural dependence problems.
• Current generation DBMS software:
  • Stores data structures, relationships between structures, and access paths.
  • Defines, stores, and manages all access paths and components.

The Database System Environment

• Defined as the organization of components that define and regulate the collection, storage, management, and use of data within a database environment.
• Composed of:
  • Hardware
  • Software
  • People
  • Procedures
  • Data

DBMS Functions

• Data dictionary management: Stores definitions of data elements and their relationships.
• Data storage management: Performance tuning ensures efficient performance.
• Data transformation and presentation: Data is formatted to conform to logical expectations.
• Security management: Enforces user security and data privacy.
• Multiuser access control: Sophisticated algorithms ensure that multiple users can access the database concurrently without compromising its integrity.
• Backup and recovery management: Enables recovery of the database after a failure.
• Data integrity management: Minimizes redundancy and maximizes consistency.
• Database access languages and application programming interfaces:
  • The query language lets the user specify what must be done without having to specify how.
    • Structured Query Language (SQL) is the standard query language supported by most DBMS vendors.
• Database communication interfaces: Accept end-user requests via multiple different network environments.

Managing the Database System: A Shift in Focus

• Disadvantages of database systems:
  • Increased costs
  • Management complexity
  • Maintaining currency
  • Vendor dependence
  • Frequent upgrade/replacement cycles

Preparing for Your Database Professional Career

Summary

• Data consists of raw facts and is usually stored in a database.
• Database design defines the structure, and database types can be classified according to number of users, location, data usage, and structure.
• Databases evolved from manual and computerized file systems, but file system data management has limitations.
• DBMSs were developed to address the file system's inherent weaknesses.