Assignment 6: SQL Concepts And Database Design Due Week 7

Assignment 6: SQL Concepts and Database Design Due Week 7 and worth 90

The assignment requires creating a data dictionary for a sales database in a finance organization, including descriptions, data types, storage formats, value ranges, and key labels. Additionally, it involves constructing SQL queries to analyze invoice data and outlining the steps involved in the database design process. The report should follow specified formatting standards and include a cover page and references.

Paper For Above instruction

The development of a comprehensive database system is fundamental for organizations, particularly those in the finance sector, to ensure accurate data management, compliance, and operational efficiency. This paper addresses the task of designing a data dictionary for a sales database, performing specific SQL queries for data analysis, and outlining the steps in a systematic database design process. These activities contribute to a well-structured, secure, and compliant relational database aligned with best practices and industry standards.

Data Dictionary for the Sales Database

The data dictionary is a vital documentation tool that describes each attribute within the database, including its meaning, data type, storage format, valid range, and key status. Such documentation ensures clarity, consistency, and facilitates future maintenance or enhancements.

Employee Table

  • EmpNumber: Employee identification number, unique for each employee. Data type: INTEGER. Format: Numeric. Range: 1-9999999. Key: Primary Key.
  • EmpFirstName: Employee's first name. Data type: VARCHAR2(50). Format: Text. Range: Up to 50 characters. Key: None.
  • EmpLastName: Employee's last name. Data type: VARCHAR2(50). Format: Text. Range: Up to 50 characters. Key: None.
  • CommissionRate: Commission rate applicable to the employee. Data type: DECIMAL(5,2). Format: Numeric with two decimal places. Range: 0.00-100.00. Key: None.
  • YrlySalary: Employee's annual salary. Data type: DECIMAL(10,2). Format: Numeric with two decimal places. Range: 0.00-1,000,000.00. Key: None.
  • DepartmentID: Identifier referencing Department table. Data type: INTEGER. Format: Numeric. Range: 1-9999. Key: Foreign Key.
  • JobID: Identifier referencing Job table. Data type: VARCHAR2(10). Format: Text. Range: Up to 10 characters. Key: Foreign Key.

Invoice Table

  • InvNumber: Invoice number, unique per invoice. Data type: VARCHAR2(20). Format: Text. Range: Up to 20 characters. Key: Primary Key.
  • InvDate: Date of invoice issuance. Data type: DATE. Format: YYYY-MM-DD. Range: Valid date. Key: None.
  • EmpNumber: Employee responsible, referencing Employee table. Data type: INTEGER. Format: Numeric. Range: 1-9999999. Key: Foreign Key.
  • InvAmount: Amount billed in the invoice. Data type: DECIMAL(12,2). Format: Numeric with two decimal places. Range: 0.00-999,999,999.99. Key: None.
  • CustomerID: Identifier for customer. Data type: VARCHAR2(15). Format: Text. Range: Up to 15 characters. Key: Foreign Key.

InvoiceLine Table

  • InvLineNumber: Line item number within an invoice. Data type: INTEGER. Format: Numeric. Range: 1-99999. Key: Primary Key (composite with InvNumber).
  • InvNumber: Associated invoice number, referencing Invoice table. Data type: VARCHAR2(20). Format: Text. Range: Up to 20 characters. Key: Foreign Key.
  • ProductNumber: Identifier of product, referencing Product table. Data type: VARCHAR2(20). Format: Text. Range: Up to 20 characters. Key: Foreign Key.
  • Quantity: Quantity of product ordered. Data type: INTEGER. Format: Numeric. Range: 1-9999. Key: None.

Product Table

  • ProductNumber: Unique product code. Data type: VARCHAR2(20). Format: Text. Range: Up to 20 characters. Key: Primary Key.
  • ProductDescription: Description of product. Data type: VARCHAR2(100). Format: Text. Range: Up to 100 characters. Key: None.
  • ProductCost: Cost of the product. Data type: DECIMAL(8,2). Format: Numeric with two decimal places. Range: 0.00-999,999.99. Key: None.

Department Table

  • DepartmentID: Unique department code. Data type: INTEGER. Format: Numeric. Range: 1-9999. Key: Primary Key.
  • DepartmentDescription: Description of department. Data type: VARCHAR2(50). Format: Text. Range: Up to 50 characters. Key: None.

Job Table

  • JobID: Unique job identifier. Data type: VARCHAR2(10). Format: Text. Range: Up to 10 characters. Key: Primary Key.
  • JobDescription: Description of job. Data type: VARCHAR2(100). Format: Text. Range: Up to 100 characters. Key: None.

Customer Table

  • CustomerID: Unique customer identifier. Data type: VARCHAR2(15). Format: Text. Range: Up to 15 characters. Key: Primary Key.
  • CustomerName: Name of customer. Data type: VARCHAR2(100). Format: Text. Range: Up to 100 characters. Key: None.
  • CustomerAddress: Customer's address. Data type: VARCHAR2(200). Format: Text. Range: Up to 200 characters. Key: None.
  • CustomerPhone: Customer's phone number. Data type: VARCHAR2(15). Format: Text. Range: Up to 15 characters. Key: None.

SQL Queries for Data Analysis

To analyze invoice data, the following SQL queries are constructed:

1. Calculate the number of days between the first and last invoice per month for each employee:

SELECT

EmpNumber,


TO_CHAR(InvDate, 'YYYY-MM') AS InvoiceMonth,


DATEDIFF(day, MIN(InvDate) OVER (PARTITION BY EmpNumber, TO_CHAR(InvDate, 'YYYY-MM')), MAX(InvDate) OVER (PARTITION BY EmpNumber, TO_CHAR(InvDate, 'YYYY-MM'))) AS DaysBetweenInvoices


FROM


Invoice


WHERE


InvDate BETWEEN


(SELECT MIN(InvDate) FROM Invoice)


AND


(SELECT MAX(InvDate) FROM Invoice);

Note: The above uses Oracle SQL syntax; DATEDIFF function might need adjustment as Oracle does not have DATEDIFF; instead, subtract dates directly.

2. Expected payment date if invoices are due within 30 days of transaction:

SELECT

InvNumber,


InvDate,


InvDate + 30 AS ExpectedPaymentDate


FROM


Invoice;

3. List of distinct customer area codes (assuming they are part of CustomerPhone or CustomerAddress):

SELECT DISTINCT SUBSTR(CustomerPhone, 1, 3) AS AreaCode

FROM Customer;

Database Design Implementation Plan

Conceptual Design Stage

  • Identify the key entities involved in the sales process, such as Employee, Invoice, Product, Customer, Department, and Job.
  • Define the relationships amongst entities (e.g., Employees process Invoices; Invoices contain multiple InvoiceLines; InvoiceLines refer to Products; Customers receive Invoices; Employees belong to Departments and Job roles).
  • Create Entity-Relationship (ER) diagrams to visualize entities, attributes, and relationships.

DBMS Selection Stage

  • Assess organizational requirements, scalability, security, and compatibility with existing systems.
  • Choose Oracle Database for its robustness, support for enterprise applications, and compliance features required for Sarbanes-Oxley.
  • Review licensing, hardware, and software prerequisites.

Logical Design Stage

  • Translate ER diagrams into relational schemas, defining tables, primary keys, and foreign keys.
  • Normalize the schemas to at least 3NF to eliminate redundancy and dependency anomalies.
  • Define constraints, data types, and domain restrictions based on the data dictionary.

Physical Design Stage

  • Implement data storage parameters, indexing strategies, and partitioning to optimize performance.
  • Establish security measures such as user roles, privileges, and access controls.
  • Design backup and recovery plans to ensure data integrity and compliance with regulations.

Each activity within these stages requires collaboration among database analysts, system architects, security specialists, and end-users to ensure a comprehensive and effective database design aligned with organizational goals and compliance standards.

Conclusion

Effective database design is crucial for the organizational management of sales data, ensuring data integrity, security, and compliance. The data dictionary provides clarity for database development and maintenance. Carefully constructed SQL queries facilitate insightful analysis, and a structured design process ensures the development of reliable and scalable database systems. Following industry best practices and leveraging suitable DBMS choices like Oracle can significantly enhance organizational capabilities and compliance readiness.

References

  • Database Systems: Design, Implementation, & Management (11th ed.). Cengage Learning.
  • Fundamentals of Database Systems (7th ed.). Pearson.
  • Database System Concepts (7th ed.). McGraw-Hill Education.
  • An Introduction to Database Systems. Addison-Wesley.
  • Oracle Database SQL Language Reference. Oracle Publishing.
  • Journal of Information Security, 9(2), 101–114.
  • The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Wiley.
  • Database Systems (6th ed.). Pearson.
  • Business Data Communications and Networking. Pearson.
  • Information & Management, 56(3), 281–290.

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