IT 233: Business Information Systems
By the end of this chapter, you will be able to:
Before databases, every application stored its own data in separate files.
Click a statement to select it, then click the correct zone to classify it.
A modern approach that creates a centralized, shared repository of data.
The goal is to create a "single source of truth" for the entire organization.
A logically coherent collection of related data.
The software that manages and controls access to the database.
Examples of DBMS: MySQL, Oracle, Microsoft SQL Server, PostgreSQL
Applications and users don't touch the data directly. They go through the DBMS.
Normalization is the process of splitting data into well-designed tables so each fact is stored only once.
Library loans: MemberName, MemberPhone, BookTitle, Author, LoanDate
A member who borrows 20 books has their phone number stored 20 times.
Members(MemberID, Name, Phone)Books(BookID, Title, Author)Loans(LoanID, MemberID, BookID, LoanDate)
Change the phone number once, and every loan sees it.
Normalization is how the database approach actually minimizes redundancy.
Data is stored once. An update in one place is an update for everyone.
This creates a "Single Source of Truth", ensuring all departments use the same, correct data.
Centralized data is easy to share across departments, providing a holistic view of the business.
The DBMS provides a sophisticated security framework.
The DBMS can enforce rules to ensure data quality.
Example Rule: An `order_quantity` field must be a positive number. The DBMS will reject any attempt to enter a negative value.
Fill in the form. The DBMS will enforce data integrity rules before accepting the transaction.
The most popular database model. Data is organized into tables (relations).
A collection of rows and columns.
Represents a single item or entity (e.g., one customer).
Represents a characteristic of that entity (e.g., customer name).
Example: A `Customers` Table
CustomerID | FirstName | LastName | City
-----------|-----------|-----------|-----------
101 | Ram | Thapa | Kathmandu
102 | Sita | Sharma | Pokhara
Click a customer row to highlight their related orders via the Foreign Key (FK).
| CustomerID (PK) | Name | City |
|---|---|---|
| C001 | Ram Thapa | Kathmandu |
| C002 | Sita Sharma | Pokhara |
| C003 | Bikash Rai | Biratnagar |
| OrderID | CustID (FK) | Product | Amount |
|---|---|---|---|
| O101 | C001 | Laptop | Rs.65,000 |
| O102 | C002 | Mobile | Rs.28,000 |
| O103 | C001 | Headphones | Rs.3,500 |
| O104 | C003 | Tablet | Rs.45,000 |
| O105 | C002 | Charger | Rs.1,500 |
Tables are linked together using special columns called keys.
A unique identifier for each row in a table. No two rows can have the same PK.
Example: `CustomerID` in the `Customers` table.
A primary key from one table that is placed in another table to create a link.
Example: `CustomerID` in the `Orders` table.
This link allows us to see all orders placed by a specific customer!
Nepal's National ID card follows a similar idea.
Table: Hotel_Booking — Thamel Hotel, Kathmandu. Click PK, FK, or Regular for each column.
Before building, you must design. This is done with a data model.
Data Model: An abstract diagram that illustrates the data structure and relationships between different pieces of data.
A common tool for this is the Entity-Relationship Diagram (ERD).
ERDs visually represent the database structure using three main components:
The "things" we store data about.
e.g., Customer, Product, Order
The properties or characteristics of an entity.
e.g., CustomerName, ProductPrice
How entities are connected to each other.
e.g., A Customer `places` an Order.
The database approach is the backbone of modern digital services.
A central database stores `Products`, `Customers`, and `Orders`. This single source of truth ensures your cart is accurate and sellers know what to ship.
Your `UserID` (Primary Key) links your account to all your `Transactions`. The DBMS ensures security and data integrity for every payment.
A national database links `Vehicle` information to `Owner` information using keys, helping manage taxes ("blue book") and ownership records efficiently.
Context: Khalti digital wallet. Click a term to select it, then click the correct bucket.
| Type | Meaning | Example |
|---|---|---|
| One-to-One (1:1) | Each A has exactly one B | A country has one capital city |
| One-to-Many (1:M) | One A has many Bs | One department employs many teachers |
| Many-to-Many (M:N) | Many As relate to many Bs | Students take many courses; each course has many students |
A 1:M link puts the FK on the "many" side. An M:N link needs a third, linking table.
Exam Long Q2, step by step. Illustrative data.
Student(StudentID PK, Name, Program)
Course(CourseCode PK, Title, Credits)
Enrollment(EnrollID PK, StudentID FK, CourseCode FK, Semester, Grade)Exam tip: name the entities, state the relationship, list each table with PK and FK marked, then give one sample row.
Short answer
Long answer
Revise the answers in the full note.
Any questions?
Next Up: Unit 3.4 - Understanding Big Data and the Five V's