Week 1 Lecture - DB & DB Env

Page 1: Database Systems Overview

• Course Code: COM162

• Introduction to Databases and Database Environment.

Page 2: Learning Objectives

• Understand common uses of database systems.

• Learn the limitations of file-based systems compared to databases.

• Distinguish between databases and database management systems (DBMS).

• Identify components and roles within the database environment.

• Explore ANSI-SPARC three-level architecture.

• Comprehend logical and physical data independence.

• Differentiate between DDL (Data Definition Language) and DML (Data Manipulation Language).

• Recognize the significance of data models and conceptual modelling.

• Understand client-server architecture and its advantages for DBMS.

Page 3: Importance of Databases

• Databases are essential for modern applications and systems.

• They organize information, bringing order to digital chaos.

• Databases are crucial gatekeepers of information power in contexts from social media to finance.

• Relational databases revolutionized data storage, management, and retrieval.

Page 4: Historical Significance of Databases

• The evolution of databases over 30+ years has significantly impacted society and the economy.

• They are a key development in software engineering, affecting organizational operations.

• Advances in hardware and communications technologies (e.g., Internet and e-commerce) have boosted database importance.

Page 5: Applications of Databases

• Common use cases include:

  • Supermarket purchases

  • Credit card transactions

  • Holiday bookings

  • Library management

  • Insurance transactions

  • Internet searches

  • University studies

Page 6: File-Based Systems

• The file-based system is the ancestor of modern databases, now considered largely outdated.

• It consists of applications that independently manage their data.

• Typically limited to small-scale applications without complex data needs.

Page 7: Challenges of File-Based Systems

• Difficulty arises when needing to cross-reference information across files.

• Example challenges:

  • Querying specific features like "three-bedroom properties with a garage."

  • Calculating averages (e.g., average rent).

  • Generating total salary reports easily.

Page 8: File-Based Processing

• Departments access their files via dedicated application programs.

• Each program handles its own data entries, maintenance, and reports.

• The application's code defines the physical structure and data storage.

Page 9: Limitations of File-Based Approach

• Separation and isolation of data across programs leads to:

  • Users may miss out on useful, cross-application data.

  • Duplication of data wastes resources and can create inconsistencies.

Page 10: Issues with Data Dependence

• Changes to data structures in file-based systems are complex and labor-intensive.

• Modifications require all related programs to be updated, risking errors.

Page 11: Incompatible File Formats

• Different application programs may not work well together due to varied file formats.

• Fixed queries lead to proliferation of specific application programs with limited scope.

Page 12: The Database Approach

• The database approach addresses file-based limitations through:

  • Centralizing data definition independent of application programs.

  • Implementing controls over data access and manipulation.

Page 13: Characteristics of a Database

• A database serves as a large, integrated repository for data used by multiple departments.

• Data definitions are distinct from application programs, allowing flexibility in modifications.

• Essential components include:

  • Entities: distinct objects like people or events.

  • Attributes: properties describing the entities.

  • Relationships: associations among entities.

Page 14: Database Management System (DBMS)

• A DBMS interacts with applications and the database, offering functions such as:

  • Data storage, retrieval, and updates.

  • Providing user-accessible catalogs.

  • Supporting transactions and ensuring data consistency.

Page 15: Continued Functions of DBMS

• Additional functions include:

  • Recovery services for data integrity.

  • Authorisation and security services to protect data.

  • Integration with communication software for data sharing.

Page 16: Database Interaction

• Users communicate with the database through various application programs.

• The DBMS manages the data's physical structure and storage, not the applications directly.

Page 17: Data Overview and Applications

• Illustration showing integration of various applications with the DBMS.

• Confirming that a centralized database facilitates coordinated access without redundant data.

Page 18: DBMS Components

• Key components of a DBMS include:

  • Programmers

  • Database administrator (DBA)

  • Application programs and Queries

  • Database schema and management utilities

Page 19: DBMS Environment Components

• Main elements in the DBMS environment:

  • Hardware: Ranging from PCs to networked systems.

  • Software: DBMS, operating systems, and relevant application software.

  • Data: Information utilized by the organization, encapsulated in a schema.

  • Procedures: Governance rules and guidelines for DB usage.

  • People: Stakeholders including developers and end-users.

Page 20: Advantages of DBMS

• Control of data redundancy and enhanced data consistency.

• Allows for increased information retrieval from integrated data.

• Shared data resources enhance inter-departmental collaboration.

• Improved integrity guarantees validity across data stored.

Page 21: Further Benefits of DBMS

• Enhanced security at the database level, unlike isolated files.

• Standardized data processes enforced across the organization.

• Improved productivity and resource management aided with centralized control.

Page 22: More DBMS Advantages

• DBA control helps balance resource use effectively.

• Enhanced data access and system responsiveness.

• Improved maintenance through data independence, limiting impact of changes.

Page 23: Disadvantages of DBMS

• Complexity in design and maintenance necessitates skilled knowledge.

• Storage size demands and potential high costs for DBMS solutions.

• Transitioning from existing systems may incur additional costs and performance issues.

Page 24: Roles in Database Environment

• Data Administrator (DA): Manages data resources and strategic planning.

• Database Administrator (DBA): Handles database design, implementation, security, and performance.

• Further reading on the roles of DA and DBA recommended.

Page 25: Database Design Roles

• Logical Database Designer: Focuses on data structure and integrity.

• Physical Database Designer: Maps logical structures to physical formats.

• Application Developers: Create programs enabling user functionality.

• End-Users: Utilize the database that meets their needs.

Page 26: History of Database Systems

• 1960s: Hierarchical and network data models.

• 1970s: Emergence of the relational model with SQL.

• 1990s: Growth in object-oriented models and data warehousing.

• 2000s: Rise of NoSQL databases for unstructured data.

Page 27: Emerging Database Trends

• Content Addressable Storage (CAS): Simplifies data retrieval by description rather than location.

• AI and Natural Language Processing: Users can interact through natural language queries.

• Scalable Data Mining Algorithms: Enhancing large dataset processing capabilities.

Page 28: Mobile and AI in Databases

• Trends include mobile database accessibility and web service integration.

• Advancements in security through computer forensics and self-tuning systems.

Page 29: ANSI-SPARC Three-Level Architecture

• The ANSI-SPARC framework outlines three abstraction levels:

  1. External Level: User view of the database.

  2. Conceptual Level: Community data view and relationships.

  3. Internal Level: Physical data storage representation.

Page 30: ANSI-SPARC Overview

• Introduced by ANSI in 1975, forming a foundation for most DBMS designs.

Page 31: Comparative Levels in ANSI-SPARC

• Differences among the levels emphasize the concept of multiple external views relating to one conceptual view.

Page 32: Objectives of Three-Level Architecture

• Uniform data access, autonomy from changes across schema levels, and DBA flexibility in modifications without user impact.

Page 33: Data Independence Objectives

• Logical Data Independence: Changes to the conceptual schema should not affect external schemas.

Page 34: Continued Data Independence

• Physical Data Independence: Modifications to internal structures should not require external or conceptual schema changes.

Page 35: Visual Model of Data Independence

• Illustrates mappings among external schemas, conceptual schema, and internal schema.

Page 36: Database Languages Overview

• DDL: Description, naming, and constraints of entities in the database.

• DML: Operations for data querying, insertion, modification, and deletion.

Page 37: Fourth Generation Languages (4GL)

• Includes SQL, form and report generators, and application generators designed for ease of use.

Page 38: Data Model Structure

• A coherent data model should clarify organizational data through:

  • Structural rules

  • Allowed operations

  • Integrity rules

Page 39: Categories of Data Models

• Object-Based Models: Utilize entities and their relationships.

• Record-Based Models: Include relational and hierarchical structures.

Page 40: Conceptual Modelling Process

• Conceptual modelling captures organizational data requirements accurately and comprehensively.

Page 41: Client-Server Architecture

• Clients manage interfaces while servers store the database; advantages include better access, performance gains, reduced costs, and enhanced consistency.

Page 42: Summary of Lecture

• Review of applications, distinctions between file-based and database approaches, role of DBMS, architecture models, data independence, and the advantages and disadvantages associated with DBMS.