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The Blood Bank Management System (BBMS) is designed to streamline and manage the various operations of a blood bank efficiently. This system is implemented using a relational database, and the following DDL and DML

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Blood Bank Management System Overview

Introduction

The Blood Bank Management System (BBMS) is designed to streamline and manage the various operations of a blood bank efficiently. This system is implemented using a relational database, and the following is a comprehensive case study that covers the database design and the Data Definition Language (DDL) and Data Manipulation Language (DML) statements used in the system.

Database Design

  • BloodGroups Table:

    • Holds information about different blood groups.
    • Columns: BGroupID, GroupName.
  • Donors Table:

    • Stores details of blood donors.
    • Columns: DonorID, FirstName, LastName, Age, Gender, BGroupID, ContactNumber, Email, MedicalReport, HemoglobinLevel, BloodPressure, DonarState, DonarAddress, LastDonationDate.
  • Patients Table:

    • Contains information about patients needing blood.
    • Columns: PatientID, FirstName, LastName, Age, Gender, BGroupID, Disease, ContactNumber, Email, PatientState, PatientAddress, MedicalHistory, HemoglobinLevel, BloodPressure.
  • BloodBanks Table:

    • Stores data about different blood banks.
    • Columns: BloodBankID, BloodBankName, BloodBankAddress, BloodBankContact.
  • BloodStocks Table:

    • Manages the stock of blood available in the blood bank.
    • Columns: StockID, BGroupID, QuantityInMilliliters, ExpiryDate, DonorID.
  • CrossMatch Table:

    • Records cross-matching information between donors and patients.
    • Columns: CrossMatchID, PatientID, DonorID, StockID, CrossMatchResult, CrossMatchDate, Remarks.
  • BloodDonations Table:

    • Tracks blood donations made by donors.
    • Columns: DonationID, DonorID, PatientID, DonationDateTime, BGroupID, QuantityInMilliliters.

DDL Statements

Defines the structure of the database and its tables.

  • Create Database
  • Create BloodGroups Table
  • Create Donors Table
  • Alter Donors Table
  • Create Patients, BloodBanks, BloodStocks, CrossMatch, and BloodDonations Tables
  • Alter CrossMatch Table
  • Delete a Column from CrossMatch Table
  • Delete a Table
  • Add Non-Clustered Index on BloodDonations Table
  • Create Views
  • Create Stored Procedures
  • Create Triggers
  • Create Functions

DML Statements

Manages the data within the tables.

  • Insert Data into BloodGroups Table
  • Insert Data into Donors Table
  • Insert Data into Patients Table
  • Insert Data into BloodBanks Table
  • Insert Data into BloodStocks Table
  • Insert Data into CrossMatch Table
  • Insert Data into BloodDonations Table
  • Retrieve Data from BloodGroups Table
  • Retrieve Data from Donors Table
  • Retrieve Data from Patients Table
  • Retrieve Data from BloodStocks Table
  • Retrieve Data from BloodBanks Table
  • Retrieve Data from CrossMatch Table
  • Retrieve Data from BloodDonations Table
  • Retrieve Only Male Donors
  • Retrieve all Donors Whose Blood Group is A+/A- or any
  • Retrieve Donors by their state
  • Format string data using literal values from Donors table
  • Uses of LEFT Function
  • Calculate Blood Donation Days
  • Find out a Patient by their ID
  • Retrieve last 3 Donors
  • Uses of BETWEEN keyword JOINING TWO TABLES
  • Uses of Wildcard JOIN WITH CORRELATION NAMES
  • Use of GROUP BY and ROLLUP Clause
  • Show Donors from 4 to 8 / USES OF OFFSET AND FETCH NEXT
  • Justify Non-Clustered Index
  • Justify Updatable View
  • Justify Read-Only View
  • Justify Encrypted View
  • Check Stored Procedure
  • Stored Procedure by Output Parameter
  • Check Stored Procedure for Insert / Update / Delete (DML Statement)
  • Select Functionality
  • INSERT Functionality
  • UPDATE Functionality
  • DELETE Functionality
  • Justify After Delete Trigger
  • Execution of Scalar Function
  • Example usage of the Table-Valued Function
  • Execution usage of the Multi-Statement Function

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The Blood Bank Management System (BBMS) is designed to streamline and manage the various operations of a blood bank efficiently. This system is implemented using a relational database, and the following DDL and DML

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