Umuc Data 620 Assignment 52: SQL Order And Group

Umuc Data 620 Assignment 52 Sql Order And Group

There are two things to turn in here. First, you will submit a SQL script file showing your answers for all of the problems below, based on the template provided. Name it “XXXâ€Assignmentâ€5â€2.sqlâ€, where XXX is your initials or your name. Second, you will take screenshots of your results and insert them into this document in the space provided after each question.

Display the product name, product number, order number, and the order state for all the orders where the OrderTbl state is Colorado. Sort the results ascending by product name. Do not group the results by anything.

Write a sentence: how many records do you have, and do you have any duplicate product names? Why might this be? Then, include a screenshot of your results and your SQL code for this problem.

Write a new query to display only the product name, product number, and order state for all orders where the OrderTbl state is Colorado. Do not use the GROUP BY command. Make the query print only distinct (unique) product names, sorted ascending by product name.

Write a sentence: how many records do you have, and do you have any duplicate product names? Why might this be? Additionally, explain the difference between this query and the previous one, especially focusing on the use of SELECT DISTINCT. Attach a screenshot and the SQL code for this problem.

For each employee with a commission less than 0.04, compute the number of orders taken. The result should include the employee number, last name, commission rate, and total number of orders taken by that employee. Each employee should be listed only once, with their total number of distinct orders. Attach a screenshot and the SQL code for this problem.

Paper For Above instruction

This paper presents SQL queries and analyses related to an Order Entry database, focusing on advanced data retrieval using ORDER BY and GROUP BY clauses, as well as the use of DISTINCT for data deduplication. The tasks involve extracting specific data sets, understanding data nuances such as duplicates, and performing aggregate calculations to gain insights on employee activities and order details. The SQL queries are constructed in accordance with the provided assignment requirements, emphasizing clarity, accuracy, and proper use of SQL functions and clauses.

Problem 1: Orders in Colorado with Full Details

The first query aims to retrieve comprehensive details about all orders where the order's state is Colorado. Specifically, it fetches the product name, product number, order number, and order state, ordering the results alphabetically by product name. This query does not employ GROUP BY, thus displaying each record that matches the criteria, including potential duplicates.

The SQL statement for this task is as follows:

SELECT ProductName, ProductNumber, OrdNo, State
FROM OrderTbl
WHERE State = 'Colorado'
ORDER BY ProductName ASC;

Executing this query provides a list of all relevant orders sorted by product name. The total number of records indicates how many orders for Colorado are present in the database. If there are duplicate product names, it suggests that the same product appears in multiple orders, which is common in order data where the same item can be purchased multiple times across different transactions.

Reasoning for duplicates includes repetitive customer orders, multiple transactions for the same product, or data entry redundancies. The presence of duplicate product names highlights the importance of using data aggregation or filtering techniques to analyze unique products if needed.

Results Analysis: Let's suppose the query retrieved 45 records, with 15 unique product names, indicating that some product names are listed multiple times, each corresponding to an individual order transaction.

Problem 2: Unique Products Ordered in Colorado

The second query refines the previous results by displaying only distinct product names, along with their product numbers and order states, specifically for orders from Colorado. It uses SELECT DISTINCT to eliminate duplicate product name entries. The results are sorted by product name in ascending order.

The SQL code is:

SELECT DISTINCT ProductName, ProductNumber, State
FROM OrderTbl
WHERE State = 'Colorado'
ORDER BY ProductName ASC;

This query ensures that each product appears only once, even if it was ordered multiple times. As a result, the total record count reflects the number of unique products ordered in Colorado, regardless of how many times each product was purchased.

The reasoning behind the difference from the first query is that SELECT DISTINCT filters out duplicate rows based on the selected columns. In this context, even if multiple orders involve the same product, only one record per product will be shown.

Results Explanation: For example, the query might return 15 records, each representing a different product, with 15 unique product names in the Colorado orders. Duplicates are eliminated because of the DISTINCT clause.

Problem 3: Employee Orders with Low Commission

The third query focuses on employees with a commission rate less than 0.04. It calculates the total number of distinct orders each such employee has taken, displaying their employee number, last name, commission rate, and the count of orders. The query groups the data by employee, ensuring each employee appears only once, with their aggregate orders count.

The SQL statement is:

SELECT Employee.No AS EmployeeNumber, Employee.LastName, Employee.CommissionRate,
COUNT(DISTINCT OrderTbl.OrdNo) AS TotalOrders
FROM Employee
JOIN OrderTbl ON Employee.No = OrderTbl.EmpNo
WHERE Employee.CommissionRate 
GROUP BY Employee.No, Employee.LastName, Employee.CommissionRate;

Executing this query provides insights into employees earning lower commissions and their workload in terms of order processing. Using COUNT(DISTINCT OrdNo) ensures that multiple entries for the same order are not double-counted.

Results Analysis: Assume the output shows three employees, each with their respective order counts: Mickey Mouse with 5 orders, Minnie Mouse with 3, and Donald Duck with 4. This helps management assess the performance and workload distribution among employees with lower commission rates.

Conclusion

The SQL tasks demonstrate the importance of ordering, filtering, and deduplication in data analysis. The use of ORDER BY helps organize the data for clarity, while DISTINCT and GROUP BY serve to summarize and analyze data effectively. These techniques are vital in real-world data management, enabling precise insights and informed decision-making.

References

• Elmasri, R., & Navathe, S. B. (2015). Fundamentals of Database Systems (7th ed.). Pearson.