Imagine That You Work For A Finance Industry-Based Organizat

Imagine That You Work For A Finance Industry Based Organization Your

Imagine that you work for a finance industry-based organization. Your organization is looking to submit its database design documentation to an evaluation team in order to meet Sarbanes-Oxley (SOX) compliance. You have been assigned to assist in preparing the documentation of the organization’s sales database. You are asked to propose a data dictionary that can be used to document the following: Employee ( EmpNumber , EmpFirstName, EmpLastName, CommissionRate, YrlySalary, DepartmentID, JobID) Invoice ( InvNumber , InvDate, EmpNumber, InvAmount, CustomerID) InvoiceLine ( InvLineNumber , InvLineNumber, InvNumber, ProductNumber, Quantity) Product ( ProductNumber , ProductDescription, ProductCost) Department ( DepartmentID , DepartmentDescription) Job ( JobID , JobDescription) Customer ( CustomerID , CustomerName, CustomerAddress, CustomerPhone)

Create a three to four (3-4) page paper in which you: Create a data dictionary that includes the following: A description of the content for each field The data type of each field The format the data will be stored as in the field The range of value for the field A label, as required, if the attribute is a primary key or foreign key.

Imagine that you are asked to identify the number of days that exist between the first invoice and last invoice for each month and complete the following: Construct a query that will show the number of days that exist between the first invoice and last invoice, for each month, for each employee, using the DATEDIFF function. Be sure to provide the SQL script that will carry out this function. Construct a query to show the expected payment date if invoices are due within 30 days of transaction. Construct a query that will show distinct area codes of the customers. Create a plan of the necessary activities that would be required to implement a valid database design process by including the following: Steps in the conceptual design stage Steps in DBMS selection stage Steps in logical design stage Steps in physical design stage Task details of each activity within each stage.

Paper For Above instruction

Imagine That You Work For A Finance Industry Based Organization Your

Introduction

In the realm of financial organizations, robust database management systems are essential for ensuring compliance with regulatory standards such as the Sarbanes-Oxley Act (SOX). The creation of a comprehensive data dictionary, alongside effective SQL queries and a structured design plan, is fundamental in establishing a reliable, secure, and auditable database environment. This paper provides a detailed data dictionary for a sales database, SQL queries for specific analytical requirements, and a systematic approach to the database design process.

Data Dictionary for the Sales Database

The data dictionary serves as a reference for understanding the structure and constraints of each attribute within the database. It includes descriptions, data types, storage formats, value ranges, and key labels.

Employee Table

  • EmpNumber: Unique identifier for employees.

      Data Type: Integer

      Format: Numeric, no decimal

      Range: 1 to 99999

      Label: Primary Key

  • EmpFirstName: Employee’s first name.

      Data Type: Varchar(50)

      Format: Text

      Range: Up to 50 characters

      Label: -

  • EmpLastName: Employee’s last name.

      Data Type: Varchar(50)

      Format: Text

      Range: Up to 50 characters

      Label: -

  • CommissionRate: Commission percentage earned by employee.

      Data Type: Decimal(5,2)

      Format: Numeric with 2 decimal places

      Range: 0.00 to 100.00

      Label: -

  • YrlySalary: Annual salary of employee.

      Data Type: Currency / Decimal(10,2)

      Format: Numeric with 2 decimal places

      Range: 0.00 to maximum salary cap

      Label: -

  • DepartmentID: Identifier linking to Department.

      Data Type: Integer

      Format: Numeric

      Range: Valid Department IDs

      Label: Foreign Key

  • JobID: Identifier linking to Job.

      Data Type: Integer

      Format: Numeric

      Range: Valid Job IDs

      Label: Foreign Key

Invoice Table

  • InvNumber: Unique invoice number.

      Data Type: Integer

      Format: Numeric

      Range: 1 to 999999

      Label: Primary Key

  • InvDate: Date of invoice issuance.

      Data Type: Date

      Format: YYYY-MM-DD

      Range: Valid dates

      Label: -

  • EmpNumber: Employee responsible for invoice.

      Data Type: Integer

      Format: Numeric

      Range: Existing Employee IDs

      Label: Foreign Key

  • InvAmount: Total amount billed in invoice.

      Data Type: Decimal(12,2)

      Format: Numeric with 2 decimal places

      Range: >=0.00

      Label: -

  • CustomerID: Customer associated with invoice.

      Data Type: Integer

      Format: Numeric

      Range: Existing Customer IDs

      Label: Foreign Key

InvoiceLine Table

  • InvLineNumber: Line item number within invoice.

      Data Type: Integer

      Format: Numeric

      Range: 1 to maximum line items per invoice

      Label: -

  • InvNumber: Reference to invoice.

      Data Type: Integer

      Format: Numeric

      Range: Valid invoice numbers

      Label: Foreign Key

  • ProductNumber: Link to product catalog.

      Data Type: Integer

      Format: Numeric

      Range: Existing Product Numbers

      Label: Foreign Key

  • Quantity: Quantity sold in line item.

      Data Type: Integer

      Format: Numeric

      Range: >=1

      Label: -

Product Table

  • ProductNumber: Unique product identifier.

      Data Type: Integer

      Format: Numeric

      Range: 1 to maximum product number

      Label: Primary Key

  • ProductDescription: Description of product.

      Data Type: Varchar(100)

      Format: Text

      Range: Up to 100 characters

      Label: -

  • ProductCost: Cost per product unit.

      Data Type: Decimal(10,2)

      Format: Numeric with 2 decimal places

      Range: >=0.00

      Label: -

Department Table

  • DepartmentID: Unique department identifier.

      Data Type: Integer

      Format: Numeric

      Range: 1 to maximum department ID

      Label: Primary Key

  • DepartmentDescription: Department description.

      Data Type: Varchar(100)

      Format: Text

      Range: Up to 100 characters

      Label: -

Job Table

  • JobID: Unique job identifier.

      Data Type: Integer

      Format: Numeric

      Range: 1 to maximum job ID

      Label: Primary Key

  • JobDescription: Description of job role.

      Data Type: Varchar(100)

      Format: Text

      Range: Up to 100 characters

      Label: -

Customer Table

  • CustomerID: Unique customer identifier.

      Data Type: Integer

      Format: Numeric

      Range: 1 to maximum customer ID

      Label: Primary Key

  • CustomerName: Customer’s legal name.

      Data Type: Varchar(100)

      Format: Text

      Range: Up to 100 characters

      Label: -

  • CustomerAddress: Customer’s address.

      Data Type: Varchar(200)

      Format: Text

      Range: Up to 200 characters

      Label: -

  • CustomerPhone: Contact phone number.

      Data Type: Varchar(15)

      Format: Text, standardized phone format

      Range: Valid phone numbers

      Label: -

SQL Queries for Analytical Tasks

1. Number of days between the first and last invoice for each month per employee

The following SQL script calculates the difference in days between the earliest and latest invoice dates for each employee within each month:



SELECT


EmpNumber,


YEAR(InvDate) AS Year,


MONTH(InvDate) AS Month,


DATEDIFF(day, MIN(InvDate), MAX(InvDate)) AS DaysBetween


FROM


Invoice


GROUP BY


EmpNumber,


YEAR(InvDate),


MONTH(InvDate)

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

This query estimates the payment date by adding 30 days to the invoice date:



SELECT


InvNumber,


InvDate,


DATE_ADD(InvDate, INTERVAL 30 DAY) AS DueDate


FROM


Invoice

3. List of distinct customer area codes

This assumes that the customer address contains the area code, for example, in a phone number or address format. For illustration, if phone numbers contain area codes:



SELECT DISTINCT


SUBSTRING(CustomerPhone, 1, 3) AS AreaCode


FROM


Customer

Note: Adjust the SUBSTRING function based on the exact format of customer address or phone number for extracting area codes accurately.

4. Implementation plan for database design process

Steps in the Conceptual Design Stage
  • Identify the main entities involved in the sales process such as Employee, Invoice, Customer, Product, Department, and Job.
  • Define the relationships among entities, such as which employees create invoices, which products are sold, and customer details.
  • Develop a high-level Entity-Relationship Diagram (ERD) to visually map out the data model.
Steps in the DBMS Selection Stage
  • Assess organizational data needs, scalability, security features, and compliance requirements.
  • Compare potential database management systems such as Oracle, SQL Server, MySQL, and PostgreSQL.
  • Choose a system based on compatibility with existing infrastructure, support, and cost considerations.
Steps in the Logical Design Stage
  • Translate the ERD into relational schemas, defining tables, attributes, and primary/foreign keys.
  • Normalize the database to reduce redundancy and improve data integrity.
  • Establish data constraints, default values, and referential integrity rules.
Steps in the Physical Design Stage
  • Decide on storage parameters, index creation strategies, partitioning, and views to optimize performance.
  • Implement security measures including user access controls and data encryption.
  • Prepare backup and recovery plans to ensure data safety.

Conclusion

The comprehensive development of a data dictionary, precise SQL queries, and a detailed design plan are crucial for establishing a compliant and efficient sales database in a financial organization. Such systematic planning ensures data integrity, security, and operational effectiveness, aligning with Sarbanes-Oxley standards and supporting organizational decision-making.

References

  • Elmasri, R., & Navathe, S. B. (2015). Fundamentals of Database Systems (7th ed.). Pearson.
  • The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. Wiley.
  • Database Design and Relational Theory: Normalization and Data Structures for Database Design. O'Reilly Media.
  • Database System Concepts (6th ed.). McGraw-Hill.
  • Database Concepts (7th ed.). Pearson.
  • Connolly, T., & Begg, C. (2015). Database Systems: A Practical Approach to Design, Implementation, and Management. Pearson.
    • Transaction Processing: Concepts and Techniques. Morgan Kaufmann. Journal of Information Security.
  • Oracle Corporation. (2020). Oracle Database Security and Compliance. Oracle White Paper.
  • Microsoft Corporation. (2021). SQL Server Security and Compliance. Microsoft Documentation.

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