Question

Assume that a database has a table named Inventory, with the following columns: a) Write a SELECT statement that will return all of the columns from every row in table. b) Write a SELECT statement that will return the Product 10 column from every row in table. c) Write a SELECT statement that will return the Product to column and the QtyonHand column from every row in table. d) Write a SELECT statement that will return the Product 10 column only from the rows where cost is less than 17.00 . e) Write a SELECT statement that will return all of the columns from the rows where Product 10 ends with \(^{*} Z Z^{*}\)

Short answer

Question: Write different SQL SELECT statements for the Inventory table based on the following scenarios: a) Select all columns and rows. b) Select only the Product10 column. c) Select both the Product10 and QtyonHand columns. d) Select the Product10 column only for rows where the cost is less than 17.00. e) Select all columns for rows where the value in the Product10 column ends with the letter 'Z'.

Step-by-step solution

a) Select All Columns and Rows

To select all columns and rows in the Inventory table, we use the asterisk symbol (*) and the SELECT statement as follows: ```sql SELECT * FROM Inventory; ```

b) Select the Product10 Column

To select the Product10 column from every row in the table, we specify this column in the SELECT statement: ```sql SELECT Product10 FROM Inventory; ```

c) Select the Product10 and QtyonHand Columns

To select the Product10 and QtyonHand columns from every row in the table, we list both columns separated by commas in the SELECT statement: ```sql SELECT Product10, QtyonHand FROM Inventory; ```

d) Select the Product10 Column with a Condition

To select the Product10 column only for rows where the cost is less than 17.00, we use a WHERE clause in the SELECT statement to apply the given condition: ```sql SELECT Product10 FROM Inventory WHERE cost < 17.00; ```

e) Select All Columns with a Condition

To select all columns for rows where the Product10 value ends with 'Z', we use the LIKE keyword along with a WHERE clause to apply the given condition. The '%' character is used as a wildcard to match any sequence of characters: ```sql SELECT * FROM Inventory WHERE Product10 LIKE '%\(^*Z^*Z\)^*%'; ```

Key concepts

Inventory Table

An inventory table in a database is a structured way to store data related to products in inventory. This table typically includes several columns, each representing a different attribute of the items being tracked. Common columns found in an inventory table might include:

• Product ID: A unique identifier for each product.
• Product Name: The name of the product.
• QtyonHand: The quantity of the item currently in inventory.
• Cost: The cost of the item.
• Supplier: The supplier of the product.

When working with an inventory table in SQL, it's crucial to understand how these columns can be queried and manipulated to provide useful insights and data-driven decisions. Queries can return all columns, specific columns, or use conditions to filter the rows, which allows businesses to manage their stock levels effectively.

SQL Conditions

SQL conditions are used to filter records returned by a query based on specific criteria. They enable precise control over which rows from a table appear in the result set. Conditions are typically used in the SQL `WHERE` clause. Here’s how they function:

• Equality: Filter rows where the data matches exactly using `=`, e.g., `WHERE cost = 20`.
• Comparison: Use `>=`, `<=`, `<`, `>` to filter rows based on numeric or date values.
• Range: The `BETWEEN` operator selects values within a range.
• List Filter: The `IN` keyword checks if values are in a list of literal values, e.g., `WHERE ProductID IN (3, 5, 6)`.
• Pattern Match: The `LIKE` operator is used for pattern matching using wildcards, ideal for partial matches.

These conditions help in narrowing down the data to just what is required for analysis, thereby providing focused insights from the raw data.

Column Selection

Column selection in SQL is fundamental when you only need specific pieces of data from a table. This process is flexible and makes SQL queries powerful tools for data analysis. To perform column selection: Specify the column names you need in the `SELECT` statement, separated by commas, e.g., `SELECT Product10, QtyonHand FROM Inventory`. This query returns data only from the `Product10` and `QtyonHand` columns.

• Single Column: Select a single column if that's the only information required. For instance, `SELECT Product10 FROM Inventory` fetches only the `Product10` column.
• Multiple Columns: Include multiple columns to get a broader data view, like `SELECT Product10, QtyonHand FROM Inventory`.
• All Columns: The `*` symbol retrieves all columns from the table, e.g., `SELECT * FROM Inventory`.

Choosing the right columns not only simplifies the returned data but also improves the query performance by minimizing unnecessary data transfer.

Wildcard Characters

Wildcard characters in SQL are special symbols used with the `LIKE` operator in a `WHERE` clause to search for a specified pattern in a column. These are particularly handy for searching partial matches in textual data. The most common wildcards are:

• `%`: Represents zero, one, or multiple characters. For instance, `LIKE 'Z%'` would match any string starting with 'Z'.
• `_`: Represents a single character. For example, `LIKE '_A'` would match any two-character string ending in 'A'.

Wildcards are invaluable in scenarios where you want to retrieve data based on partial strings or when dealing with data that's unstructured or inconsistently formatted. For instance, selecting rows where `Product10` ends with 'ZZ' would involve a query like `SELECT * FROM Inventory WHERE Product10 LIKE '%ZZ'`. This effectively isolates only the records that match your specified pattern. When used correctly, wildcards can significantly enhance the flexibility and power of your SQL queries.