The document outlines the assessment structure and topics for a course on database systems (CSC 203), including the grading categories and lecture schedule. It details the history and development of database management systems (DBMS) from file processing systems to modern approaches, highlighting the advantages and characteristics of database systems. Key concepts such as data, information, data models, and the advantages of DBMS over traditional file processing methods are discussed.

1. Database Systems (CSC 203)
Elvis Selasi
egati@cktutas.edu.gh

2. 2
Assessment Outline
SN
ASSESSMENT CATEGORY MARKS
1
Assignments/Term papers/Project
Work/Essays
10
2
Quizzes/Lab-based Practical Work 10
3
Mid Semester Examination 20
4
End of Sem Examination 60
Total 100

3. 3
Outline
Topic Subtopics
Introduction to Database System History, Purpose, Advantages and Disadvantages
Database System Architecture
Database Environment
Types of Database Systems - Hierarchical Database Systems
- Network Database Systems
- Relational Database System
- Logical Database Systems
View of Data - Data Abstraction- Instances and Schemas
Data Models - Conceptual Models
- Graphic Models
- Declarative Models
- Relational Models
- Entity-Relational Models- Object-Oriented Models
Data Independence
Data Normalisation - 1st Normal Form
- 2nd Normal Form
- 3rd Normal Form
- Conversion from un-normalised to Normalised Form
Relational Algebra and Calculus
Database Design/Development Process

4. 4
Take Note
Lecture Periods:
◦ Tuesdays: 3:00 PM – 3:55 PM (NH1)
◦ Wednesdays: 5:00 PM – 6:55 PM (NHA1)
Assignments:
◦ Should be sent using the student’s Institutional email.
◦ Submitted on time to egati@cktutas.edu.gh /Google Class/Forms

5. 5
Introduction (Data, Information, DB, DBMS)
Data:
◦ Raw facts, figures, and statistics that are typically
collected and recorded.
◦ It can take various forms, such as numbers, text,
images, audio, or video.
◦ Data by itself may not have any particular
meaning or context.
Information:
◦ Information is processed and organized data that
has meaning and context.
◦ It is the result of analyzing, interpreting, and
presenting data in a meaningful way, making it
useful for decision making.
Database:
• Structured collection of data that is organized
and stored systematically.
• It is designed to efficiently store, retrieve, and
manage large amounts of data.
• Databases provide a structured framework for
storing and organizing data, which enables
efficient data manipulation and retrieval.

6. 6
Introduction (Data, Information, DB, DBMS)
Database Management Systems (DBMS):
• A software application that allows users to define, create, and manipulate databases.
• It provides a set of tools and functions for managing data, including data organization,
storage, retrieval, security, and integrity.
• Examples of popular DBMSs include MySQL, Oracle Database, Microsoft SQL Server,
and PostgreSQL.
Database Systems:
• The software, hardware, and processes used to manage and interact with databases.
• Includes the database management system (DBMS) and other supporting components.

7. 7
Introduction (Data, Information, DB, DBMS)
In this table, we have data about individuals,
including their ID, name, age, gender, and occupation.
Each row represents a separate record or entry.
• Data: In this context, the raw data would be the
individual pieces of information recorded in the
table. ID, name, age, gender.
• These individual values are considered raw facts.
• Information: By organizing and
processing the raw data, we can
derive meaningful information.
• For example, we can understand that
John is a 25-year-old male software
engineer, Emily is a 30-year-old
female marketing manager, and so on.
• Analyzing the data could involve
performing calculations, aggregations,
comparisons, or drawing conclusions
from the data.
This processed data with meaning and
context becomes information.
ID Name Age Gender Occupation
1 John 25 Male Software Engineer
2 Emily 30 Female Marketing Manager
3 Michael 35 Male Sales Representative
4 Sarah 28 Female Data Analyst

8. 8
Historical Perspective
1960s
• File Processing System (FPS) was still dominant
during this period.
• The first general-purpose DBMS was designed by
Charles Bachman at G.E. in the early 1960s and
was called the Integrated Data Store.
• Formed the basis for the Network Data Model,
which was standardized by the Conference on
Data Systems Languages (CODASYL) and strongly
• influenced database systems through the 1960s.
1970s
• The use of DBMS became a commercial reality.
• IBM developed the Information Management
System (IMS) DBMS, used even today in many
major installations.
• IMS formed the basis for an alternative data
representation framework called the Hierarchical
Data Model.
• NB: Both the Network and Hierarchical Data
models are regarded as the first-generation
DBMS.

9. 9
Historical Perspective
1980s
• To overcome the limitations of the earlier models, Edgar
Codd, at IBM’s San Jose Research Laboratory, proposed
a new data representation framework called the
Relational Data Model.
• This model is considered the 2nd Generation DBMS.
• The Relational Model was positioned as the dominant
DBMS paradigm and received widespread commercial
acceptance.
• The SQL, query language for relational databases was
developed and standardized.
1990’s
• This period ushered in a new era of computing.
• Client/server computing, data warehousing, &
internet application became increasingly
important.
• Multimedia data (graphics, sound, images, and
videos) increased.
• To cope with the complex data, Object-oriented
DBs considered 3rd Generation DBMS were
introduced.

10. 10
Historical Perspective
2000 & Beyond
• The ability to manage increasingly complex data types.
• Content-addressable storage will become more popular.
• Database and other technologies, such as artificial intelligence will make
database access much easier for untrained users.
• Data mining algorithms that scale to handle very large data sets will result in
organizations being able to analyze their huge data efficiently.

11. 11
Historical Perspective

12. 12
File Processing Systems
File Processing Systems (FPS) are a way of
storing, retrieving, and manipulating data
that is present in various files.
File processing systems were an early
approach to managing and organizing data
before the advent of modern database
management systems.

13. 13
FPS – Key Characteristics
• Data is stored in independent files
of records, without using a
centralized database.
• Files are organized into a
hierarchical directory structure,
with files grouped into folders.
• Each application or program has
its own set of files that it uses for
data storage and retrieval.
• Data about the data (metadata)
is stored within the files, often in a
tabular format.
• To access data, users need to
know the entire file hierarchy and
location.

14. 14
FPS – Key Characteristics

15. 15
File Processing Systems (Pros & Cons)
Advantages of FPS:
• Cost-effective, as they require minimal setup
and usage fees.
• Easy to use, with a basic learning curve.
• Highly scalable, allowing users to easily switch
between smaller and larger files.
Disadvantages of FPS:
• Slow data access times, as users need to
navigate the file hierarchy
• Presence of data redundancy across multiple
files, leading to inconsistencies.
• Lack of data integrity mechanisms, making it
difficult to ensure data accuracy and
consistency.
• Challenges in recovering corrupted or lost data.
• Lack of concurrency control, leading to issues
with multiple users accessing the same data.
• Limited security, as anyone with file access can
read or modify the data.

16. 16
File Processing System
To address these limitations, database management systems (DBMS) were
developed, which provided a centralized and structured way of storing and
managing data, with advanced features for ensuring data integrity, security,
and performance.

17. 17
The Database Approach
In traditional file processing,
• each user defines and
• implements the files needed for a specific software application as part of
programming the application.
In the database approach,
• a single repository maintains data that is defined once and
• then accessed by various users repeatedly through queries, transactions, and
application programs.

18. 18
The Database Approach - Characteristics
Self-Describing Nature:
• The database system contains not only the database itself but also a complete
definition or description of the database structure and constraints, known as metadata.
• This metadata is stored in the DBMS catalog, which describes the structure of every
file, the type and storage format of every data item, and the various constraints and
rules on the data.
• The DBMS software can access this metadata to understand the structure of the
database.

19. 19
The Database Approach - Characteristics
Insulation between Programs and Data
• In traditional file processing, the data file structure is embedded within the
application programs. Any changes to the file structure would require changes
to all the programs that access that file.
• In the database approach, the structure of the data files is stored separately in
the DBMS catalog, providing independence between the programs and the
data.
This is known as program-data independence.

20. 20
The Database Approach - Characteristics
Data Abstraction
• The database approach provides users with a
conceptual representation of the data that hides
many of the low-level storage details.
• This data abstraction allows users to interact with
the data at a higher, more logical level without
needing to know the physical implementation
details.

21. 21
The Database Approach - Characteristics
Support for Multiple Views
• A database can provide different users with different "views" of the
data, tailored to their specific needs. These views can be subsets of the
full database or can contain derived data that is not explicitly stored.
Data Sharing and Multi-user Transaction Processing
• Allows multiple users to access and update the same data concurrently.
The DBMS implements concurrency control mechanisms to ensure data
integrity and consistency during these multi-user transactions.

22. 22
The Database Approach - Characteristics
Data Security
• Databases provide various security features, such as access control, authentication,
and encryption, to protect data from unauthorized access, modification, or deletion.
Backup and Recovery
• Databases offer reliable backup and recovery mechanisms to restore data in case
of system failures or data loss.
Scalability
• Databases are designed to handle large volumes of data and can scale up or
down as the organization's data needs change

23. 23
The Database Approach - Advantages
◦ Program-data independence
◦ Planned data redundancy
◦ Improved data consistency
◦ Improved data sharing
◦ Enforcement of standards
◦ Improved data quality
◦ Backup and recovery.
◦ Multiple user interfaces

24. 24
The Database Approach – Risk & Cost
◦ New, specialized personnel
◦ Installation and management cost and complexity.
◦ Conversion cost
◦ Need for explicit backup and recovery.