Importance of Database Design

A well-designed database is essential for any database project. It ensures data integrity, minimizes redundancy, enhances application performance, and improves user satisfaction—all critical factors for a successful project.

Investing time in database design is mandatory, as it helps prevent costly issues later in the project.

Database Design Process

The database design process consists of three key steps:

• Requirements Analysis

• Logical Design

• Physical Design

Requirements Analysis

This is the initial phase, where you collaborate closely with stakeholders to gather and analyze real-world business requirements and policies. The primary goal is to identify base objects and their relationships.

For example, in a scenario where a Client purchases a Product, we need to determine the relevant information associated with each entity. A Product may have attributes such as name and description, while a Client may have attributes such as name, client ID, address, email, and phone number. Also, A Client buying a Product involves creating a Purchase Order that contains Order Line Items.

• A Client represents an individual or business making purchases. Relevant information includes:

  • ClientID (unique identifier)

  • FullName (first and last name or business name)

  • Address (including street, city, state, and zip code)

  • Email (primary contact email)

  • PhoneNumber (primary contact number)

  • RegistrationDate (date the client was added to the system)

• A Product represents an item available for purchase. Relevant details include:

  • ProductID (unique identifier)

  • Name (product name)

  • Description (brief details about the product)

  • Price (cost of the product)

  • StockQuantity (number of available units)

  • Category (classification of the product)

• A Purchase Order represents a transaction where a client buys one or more products. It includes:

  • OrderID (unique identifier)

  • ClientID (reference to the purchasing client)

  • OrderDate (date of purchase)

  • TotalAmount (total cost of the order)

  • PaymentMethod (e.g., credit card, PayPal, bank transfer)

• An Order Line Item captures details of individual products within a purchase order:

  • OrderDetailID (unique identifier)

  • OrderID (reference to the related purchase order)

  • ProductID (reference to the purchased product)

  • Quantity (number of units purchased)

  • UnitPrice (price at the time of purchase)

Methods for Data Acquisition

There are several methods to collect and validate data:

• Reviewing existing data stores as a source of information

• Interviewing users to understand current data usage

• Gathering insights from users to identify potential improvements

Output of Requirement Analysis

The result of the requirement analysis can be a report, a data diagram, or a presentation.

Logical Design

In this phase, the findings from the previous step are translated into Entities, Attributes, and Relationships:

• Objects evolve into Entities

• Object characteristics become Attributes

• Relationships between objects are clearly defined

Considering Entity Attributes

Entities should have well-structured attributes. For example, instead of storing an address as a single field, breaking it down into components such as street name, city, state, and zip code improves data efficiency and usability.

Conceptual Blueprint for Robust Design

A solid logical design serves as the foundation for the physical database structure.

Entity Relationship Management

• Assign a unique identifier as a primary key

• Normalization to optimize data structure:

  • In OLTP (Online Transaction Processing) systems, normalization typically follows 3NF or higher to minimize redundancy.

  • In OLAP (Online Analytical Processing) systems, performance is prioritized, leading to denormalized schemas like the Star Schema for efficient querying.

Physical Design

In this final phase, the logical model is translated into an actual database structure. This involves defining tables, columns, data types, indexes, and storage requirements to ensure optimal performance and maintainability.

Implementing Tables and Attributes

• Entities identified in the logical design become tables.

• Attributes are mapped to columns with appropriate data types (e.g., VARCHAR, INT, DATE).

• Constraints such as NOT NULL, UNIQUE, and CHECK are applied to maintain data integrity.

Defining Primary and Foreign Keys

• Primary keys ensure each record is uniquely identifiable.

• Foreign keys establish relationships between tables and enforce referential integrity.

Indexing Strategies

• Indexes are created to enhance query performance, especially for frequently accessed columns.

• Consider clustered and non-clustered indexes based on query patterns.

Partitioning and Storage Optimization

• Large datasets can be partitioned to improve performance.

• Choosing between row-based or column-based storage depends on the database workload (OLTP vs. OLAP).

Security and Access Control

• Implement user roles and permissions to restrict unauthorized access.

• Encrypt sensitive data and enable audit logging for compliance.

Summary

Database design is crucial for the success of a project. The process consists of three key steps:

• Requirements Analysis: Identifying base objects, relationships, and business information.

• Logical Design: Structuring data into entities and attributes while applying normalization.

• Physical Design: Implementing the design into a database with well-defined tables and columns.

By following these steps, we ensure a structured, scalable, and efficient database system.

References

-Approach to Database Design - IBM Data Engineering - Coursera