The Blueprint for Your Data House 🏠
Before you build a house, you need a blueprint. A bad blueprint leads to a house with plumbing in the living room and no closets. A good blueprint ensures everything is logical, efficient, and can handle your family as it grows.
Database design is the blueprint for your data. This lesson walks you through the 6 essential steps to go from a simple idea to a robust, ready-to-build database schema.
Step 1: Business Rules → Conceptual Model
Everything starts with understanding the business in plain English. The Conceptual Model is a high-level sketch of your data world.
- Business Rules: Simple statements. For our OracleFlix database, a rule would be: "A customer can rent many movies. A movie can be rented by many customers."
- Identify Entities (Nouns): The key objects are **Customer**, **Movie**, and **Rental**.
- Identify Relationships (Verbs): A **Customer** `rents` a **Movie**, which is recorded as a **Rental**.
Result: A simple diagram showing boxes for entities and lines for relationships, with no technical details.
Step 2: Conceptual Model → Logical Model
Now we add more detail. The Logical Model is still platform-independent, but it defines the specific columns (attributes) and keys for each entity.
- Customer Entity: Gets attributes like `CustomerID` (Primary Key), `FirstName`, `LastName`, `Email`.
- Movie Entity: Gets attributes like `MovieID` (Primary Key), `Title`, `Genre`, `ReleaseDate`.
- Rental Entity: This linking table gets `RentalID` (PK), `CustomerID` (Foreign Key), `MovieID` (FK), `RentalDate`.
Result: A detailed diagram showing each table with its columns and keys clearly marked.
Step 3: Check with Normalization
Normalization is a formal process for minimizing data redundancy. The goal is to ensure data is stored logically, which prevents errors when data is added, updated, or deleted.
The Core Idea: Every piece of data should live in only one place. Don't write a customer's full address on every rental record; just use their `CustomerID` and look up the address when you need it.
A key rule is **Third Normal Form (3NF)**, which states that all columns in a table should depend only on the primary key. For example, a `DirectorName` shouldn't be in the `Movies` table because the director's name depends on the director, not the movie. It belongs in a separate `Directors` table.
Step 4: Pick a Platform
With a solid logical model, you can choose where to build it. The two main families are:
- Relational (SQL): MySQL, PostgreSQL, Oracle. Perfect for structured data with clear relationships, like our movie rental store. They prioritize consistency.
- NoSQL: MongoDB, Cassandra. Better for unstructured or rapidly changing data at a massive scale, like social media posts or sensor readings. They prioritize flexibility and scalability.
Step 5: Identify Datatypes
Datatypes are the rules for each column, defining what kind of data is allowed. This is where your choice in Step 4 matters, as different platforms have different names for similar types.
Common Datatypes & Platform Differences:
- Text: `VARCHAR(100)` (MySQL), `VARCHAR2(100)` (Oracle), `TEXT` (PostgreSQL)
- Integers: `INT` or `INTEGER` (most platforms)
- Decimals: `DECIMAL(10, 2)` (MySQL), `NUMBER(10, 2)` (Oracle)
- Dates: `DATE`, `DATETIME`, `TIMESTAMP` (names vary slightly)
Always check the official documentation for your chosen database platform!
Step 6: Logical Model → Physical Model
This is the final step. The Physical Model is the concrete, platform-specific implementation. You take your logical model and apply the exact datatypes and naming conventions from the platform you chose in Step 4. This becomes the final blueprint you use to write your `CREATE TABLE` statements.
Result: A final schema ready for implementation.