Assignment: Using The Employees Table Of Figure 14.6, What

Assignment #. Using the Employees table of Figure 14.6, what is the result of the following SQL query?

Using the Employees table of Figure 14.6, what is the result of the following SQL query?

SELECT * FROM Employees WHERE HoursWorked

This SQL statement retrieves all records from the Employees table where the value in the HoursWorked column is less than 100. Referring to Table 14.6, the relevant data is as follows:

Since specific HoursWorked data isn't fully provided for each employee, assuming that only the records with HoursWorked less than 100 in the actual table are returned, the query would list all such employees, including Morris Honou with a pay rate of $6 and HoursWorked presumably less than 100 (since he is included). Employees like John Kay, Frederick Takasano, and Janet Kay would also be included if their HoursWorked are below 100.

Assignment #. Using the Employees table of Figure 14.6 and the InsurancePolicies table of Figure 14.7, what is the result of the following SQL query?

Using the Employees table of Figure 14.6 and the InsurancePolicies table of Figure 14.7, what is the result of the following SQL query?

SELECT ID, PlanType FROM Employees, InsurancePolicies WHERE Birthdate > #1/01/1960# AND ID = EmployeeID;

This SQL statement performs an inner join between the Employees and InsurancePolicies tables based on matching EmployeeID with ID. It retrieves the Employee ID and Insurance PlanType for employees born after January 1, 1960.

Referring to Table 14.6, employees born after January 1, 1960, include Takasano Frederick (born 5/23/1966) and others if applicable. Assuming Table 14.7 lists insurance policies assigned to employees, the result set would contain pairs of Employee IDs and Plan Types for these employees.

For example, if Frederick Takasano (ID 171) is born after 1960 and has an insurance plan, and the insurance policy table indicates he has PlanType C issued on 2/18/1999, then the query would return:

• 171 - PlanType C

The actual output depends on the full data in Tables 14.6 and 14.7, but generally, it would include Employee IDs and their respective insurance plan types for employees born after January 1, 1960.

Sample Paper For Above instruction

The use of SQL for querying employee-related data is fundamental in database management systems. It allows for efficient retrieval, filtering, and joining of data from multiple tables. This paper explores specific SQL queries applied to a hypothetical Employees table, analyzing the expected results and implications of such queries.

Analysis of the First Query: Filtering Employees by Hours Worked

The first query, SELECT * FROM Employees WHERE HoursWorked , aims to extract all employee records where the number of hours worked per week (or another period) is less than 100. This type of query is essential for identifying part-time employees, employees with reduced hours, or potential anomalies in work hours data. Based on the provided data in Table 14.6, some employees, such as Morris Honou, with the lowest pay rate of $6, might also have lower hours worked. The actual output would depend on the specific HoursWorked data—if Honou's hours are below 100, his record will be included. Similarly, employees like John Kay and Frederick Takasano would be included if their hours worked are under this threshold. Analyzing such data helps HR managers understand workload distributions and identify employees with decreased workload or unusual hours.

Analysis of the Second Query: Retrieving Names and Pay Rates, Ordered by Pay

The second SQL query requests the first and last names alongside the pay rate of employees, ordering the results by pay rate in ascending order. Such a query provides insight into compensation structures, highlighting the range of pay among employees. The SQL statement would be structured as follows:

SELECT FirstName, LastName, PayRate FROM Employees ORDER BY PayRate;

Executing this query reveals which employees earn the highest and lowest wages, enabling salary benchmarking and compensation analysis. For example, employees like Morris Honou earning $6 would appear at the bottom, whereas Janet Kay earning $16 would be higher in the list. This form of data retrieval supports salary review processes and helps identify pay disparities that require further analysis.

Analysis of the Third Query: Joining Employee and Insurance Policy Data

The third query involves joining data between the Employees and InsurancePolicies tables:

SELECT ID, PlanType FROM Employees, InsurancePolicies WHERE Birthdate > #1/01/1960# AND ID = EmployeeID;

This join retrieves the Employee ID and the Insurance PlanType for employees born after January 1, 1960. It uses an inner join condition based on matching EmployeeID values and filters employees by birthdate. Referring to the data, employees like Frederick Takasano (born 1966) and others meeting this condition will be included. The output helps in understanding the insurance coverage distribution among younger employees and could assist in assessing insurance plan utilization or coverage trends.

Concluding Remarks

SQL queries serve as powerful tools for analyzing employee data, enabling organizations to extract meaningful insights from raw data. Properly structuring SQL statements to filter, project, and join datasets allows HR and management to make informed decisions regarding staffing, compensation, and benefits. Understanding the expected results of these queries emphasizes the importance of accurate data entry and maintenance in database systems, which directly impacts the quality of analytical outputs.

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