Unit III Assignment SQL Exercise

Unit III Assignment SQL Exercise In This Exercise You Will Be Typing In

In this exercise, you will be typing in SQL commands and executing them against the database that you installed in the Unit II Database exercise. Be sure that you have completed the Unit II Database exercise before attempting this SQL exercise. You should complete the following ‘Try It Out’ exercises from the Discovering SQL textbook. Be sure to re-read the sections preceding each of these, so that you understand what each exercise is accomplishing. Copy and paste your SQL statements and the results into a Word or text document.

Alternatively, you can create a screen capture of the SQL commands and the results window and paste those into the Word document. The text or Word document should contain all of the commands and results for all ten ‘Try It Out’ exercises. Be sure to label each section with the title or the page number and the step number you are performing. This will help your instructor easily identify each part. Pay close attention to the formatting of your SQL statements and the labelling, as these are part of the grading criteria.

The exercises include:

• Try It Out: Parsing Text Using SQL Built-in Functions, page 115
• Try It Out: Hunting for Leap Years
• Try It Out: Counting NULL(s) and Zeroes
• Try It Out: Constructing an AVG Function of Our Own
• Try It Out: Bringing it All Together
• Try It Out: Finding the Highest-Priced Book on the Shelf
• Try It Out: Using the Subquery in the GROUP BY…HAVING Clause
• Try It Out: INSERTing Records with a Subquery
• Try It Out: Extracting JOIN(ed) data from RDBMSs
• Try It Out: Wrapping Complexity in a View

Paper For Above instruction

This paper documents the completion of the unit III SQL exercises, emphasizing the practical application of SQL commands as instructed in the Discovering SQL textbook. The exercises build upon foundational knowledge from the previous unit’s database setup and involve executing a series of ten structured SQL tasks designed to enhance understanding of text parsing, date functions, null and zero handling, aggregate functions, subqueries, joins, and views.

Initially, the exercises focus on parsing text using built-in SQL functions. These functions include SUBSTRING, LENGTH, and other string operations that enable extracting specific parts of text stored within database fields. Practice with these functions enhances data manipulation capabilities critical in data cleaning and transformation tasks, especially when preparing data for analysis or reporting.

Next, the exercises guide users through identifying leap years within date data—a common task in date validation and time-series analysis. This involves writing date functions and conditional logic to filter records based on year calculations, confirming proficiency in handling date-related data.

Subsequently, solutions for counting NULL values and zeros are explored. This task involves understanding how to handle missing or zero data points, which often impact data quality and analysis accuracy. Strategies include using IS NULL, COUNT, and CASE expressions to count and differentiate between NULLs and zeros effectively.

The subsequent exercise emphasizes constructing custom aggregate functions, specifically creating an AVG function tailored to specific filtering criteria. This involves practicing with aggregate functions, GROUP BY clauses, and creating user-defined calculations to expand analytical capabilities.

Bringing all these skills together, the exercises include comprehensive queries that combine string parsing, date calculations, null handling, and aggregation to perform complex data analysis tasks.

Additionally, the exercises focus on finding the highest-priced book on a shelf, showcasing practical use of subqueries and ORDER BY clauses to identify maximum values within datasets. Using subqueries in GROUP BY and HAVING clauses demonstrates advanced query structuring for filtered aggregation.

The practical application continues with inserting records via subqueries—an essential technique when copying or transforming data dynamically. Efficiently inserting data based on existing table data showcases the utility of subqueries for maintaining data integrity.

Extracting joined data reflects proficiency in joining multiple tables, a core aspect of relational database querying. The exercises include pulling combined data from related tables, illustrating data relationships and retrieval strategies.

Finally, wrapping complex queries within views provides an overview of creating virtual tables that encapsulate complex logic. Views facilitate reuse, simplify complex queries, and improve database performance and security management.

In conclusion, these exercises collectively develop advanced SQL skills necessary for effective database management and analysis. They also reinforce best practices for writing clear, efficient, and maintainable SQL code—an essential competency for database administrators and analysts alike.

References

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