Design A Query That Will Allow The Finance Department To Det
Design a query that will allow the finance department to determine the commissions paid to specific employees of the sales department for the month of December
Imagine that you have been hired as a consultant to assist in streamlining the data processing of an international organization that sells high-end electronics. The organization has various departments such as payroll, human resources, finance, marketing, sales, and operations. The sales department is the only department where employees are paid a commission in addition to their yearly salary and benefits. Commission is paid by multiplying the employee’s commission rate by the total amount of product units sold.
You have access to the following data sets: Employee (EmpNumber, EmpFirstName, EmpLastName, CommissionRate, YrlySalary, DepartmentID, JobID), Invoice (InvNumber, InvDate, EmpNumber, InvAmount), InvoiceLine (InvLineNumber, InvNumber, ProductNumber, Quantity), Product (ProductNumber, ProductDescription, ProductCost), Department (DepartmentID, DepartmentDescription), and Job (JobID, JobDescription). Your task involves several components:
Paper For Above instruction
To facilitate the finance department in determining commissions for sales employees for December, I designed a SQL query that retrieves relevant employee details from the Employee table and calculates commissions based on the sales data from Invoice and InvoiceLine tables. The core logic involves filtering invoices by the specified month and year, identifying sales employees, calculating total units sold, and computing individual commissions accordingly.
Below is the validated SQL code for the query:
-- Select employees in the sales department with their commission details for December 2023
SELECT
e.EmpNumber,
e.EmpFirstName,
e.EmpLastName,
SUM(il.Quantity) AS TotalUnitsSold,
e.CommissionRate,
SUM(il.Quantity * p.ProductCost) AS TotalSalesAmount,
(SUM(il.Quantity) * e.CommissionRate) AS TotalCommission
FROM Employee e
JOIN Invoice i ON e.EmpNumber = i.EmpNumber
JOIN InvoiceLine il ON i.InvNumber = il.InvNumber
JOIN Product p ON il.ProductNumber = p.ProductNumber
JOIN Department d ON e.DepartmentID = d.DepartmentID
WHERE d.DepartmentDescription = 'Sales'
AND i.InvDate BETWEEN '2023-12-01' AND '2023-12-31'
GROUP BY e.EmpNumber, e.EmpFirstName, e.EmpLastName, e.CommissionRate;
This query effectively isolates sales employees and calculates their commissions specifically for December 2023, considering the quantity sold and the commission rate. It joins multiple tables to gather all necessary details, ensuring data accuracy and integrity.
When comparing this to the total compensation query, the key difference lies in the additional calculation of salary components versus commissions. For total compensation, the query sums the annual salary and benefits, adding the computed commissions derived above. Ensuring referential integrity across these tables necessitates maintaining primary keys such as EmpNumber for Employee, InvNumber for Invoice, and relationships like Invoice.EmpNumber to Employee. Foreign keys enforce consistent relationships, preventing orphaned records and ensuring data consistency.
An object-oriented model depicting these relationships would structure entities such as Employee, Invoice, InvoiceLine, Product, Department, and Job, with associations indicating one-to-many (1:M) relationships—for example, a department has many employees, each employee has many invoices, and each invoice has many invoice lines. Accurate mapping of attributes and relationship types is crucial for data modeling, supporting data integrity, and facilitating scalability.
In terms of leverage from Big Data technologies, the organization could utilize advanced data analytics and machine learning algorithms to analyze vast datasets. These tools can forecast product demand, optimize inventory management, and improve sales strategies. Big Data enables real-time data processing, which allows for dynamic adjustments in marketing efforts and resource allocation, ultimately enhancing organizational productivity and competitive advantage.
References
- Coronel, C., & Morris, S. (2015). Database Systems: Design, Implementation, & Management. Cengage Learning.
- Modern Database Management (12th ed.). Pearson.