**Scalar Functions**

Scalar functions operate on a single value and return a single value. They are either user-defined or a system defined function , and they perform operations involving mathematical calculation, string and data manipulation language, date and time conversion, and other types of data transformation. Both system-defined and user-defined scalar functions exist, allowing for extensive flexibility in data definition language manipulation (StudySmarter, W3Schools).

**Aggregate Functions**

Aggregate functions perform calculations on a set of values and return a single value, making them invaluable for data analysis and summary operations. These functions include AVG() (calculates the average of a set of values), COUNT() (counts the number of items in a set), SUM() (adds together all values in a set), MIN() (finds the minimum value), and MAX() (finds the maximum value). Aggregate functions are typically used in conjunction with the GROUP BY clause in SQL queries to aggregate and manipulate data from across specified groups (GeeksforGeeks, W3Resource).

**Table-Valued Functions**

Table-valued functions return a table data type that can be used in the same manner as a regular table in SQL queries. These functions are potent for complex query data or manipulations where the result needs to be utilized in further SQL operations. Table-valued functions can be classified into Inline Table-Valued Functions, which directly return default value of a table from a single SELECT statement, and Multi-Statement Table-Valued Functions, which can contain multiple T-SQL statements and provide more control over the structure of the returned database table. (SQLShack, Microsoft).

## Introduction to SQL Server Functions in T-SQL And SQL Stored Procs

In SQL, functions and procedures are both database objects used for encapsulating SQL code, but they serve distinct purposes:

**Functions**:

Functions accept parameters, perform calculations, and return a single value.

They can be used within SQL queries wherever expressions are allowed.

Functions are commonly used for calculations and transformations like summing

values or formatting dates.

They can be deterministic (always return the same result for the same input) or nondeterministic.

Examples include SUM(), AVG(), CONCAT(), and DATE_FORMAT().

**Procedures**:

Procedures are sets of SQL statements that perform one or more tasks and may include control-flow logic including try Catch statements.

They can accept input parameters and return multiple values through output parameters or result sets.

Procedures don't necessarily return a value directly; they may modify data or execute actions without returning anything.

Procedures are used for complex tasks involving multiple steps or logic, like data validation or transaction management.

Examples include stored procedures and anonymous blocks.

## Understanding Scalar Functions In SQL With Examples

Introduction to SQL Server Functions in T-SQL - Scalar functions in SQL Server play a crucial role by returning a singular value from the input provided by the user-defined function.

### GetDate() and DatePart Date functions

**Practical Use:**Â This is particularly handy for generating reports that require filtering records based on the current year (Microsoft Documentation).

**GETDATE()**Â fetches the current system date and time.

**DATEPART()**Â extracts a specific date component, such as year, month, or day.

**Example:**Â To determine the current year:

`SELECT DATEPART(year, GETDATE()) AS CurrentYear;`

### Length function query in SQL

**Practical Use:**Â This tool is useful for validating the length of input data in forms, ensuring they meet specific length criteria.

**LEN()**Â calculates the length of a given string expression, not counting any trailing spaces.

**Example:**Â To calculate the length of a string:

`SELECT LEN('Hello World') AS LengthOfString;`

**CONVERT()**Â

changes the data type of an expression to another data type, with optional style formatting.

**Practical Use:**Â It is essential for transforming data types, especially when handling data imported from external sources, to ensure compatibility with other relational databases, with relational database for storage and transform data formats.

**CAST()**Â is similar to CONVERT(), but it doesn't support style formatting.

**Example:**Â To convert a string into a date format:

`SELECT CONVERT(DATE, '20230310', 112) AS ConvertedDate;`

**SUBSTRING Function()**

**Practical Use:**Â Extracting specific segments from strings, such as extracting first names from full name fields.

**SUBSTRING()**Â retrieves a part of a specified expression.

**Example:**Â To extract a portion of a string:

`SELECT SUBSTRING('Hello World', 1, 5) AS ExtractedString;`

### Upper And Lower Function

**Practical Use:**Â Normalizing user inputs for consistent case-insensitive processing, which is particularly useful in user authentication scenarios.

**UPPER()**Â converts all characters in a given string to uppercase.

**LOWER()**Â changes all characters in a specified string to lowercase.

**Example:**Â To convert a string to uppercase:

`SELECT UPPER('Hello World') AS UppercaseString;`

**ROUND(), CEILING(), and FLOOR()**

**Practical Use:**Â These functions are crucial for financial computations, ensuring that currency values are correctly formatted for reporting purposes.

**ROUND()**Â rounds a numeric value to a specified precision.

**CEILING()**Â gives the smallest integer greater than or equal to the given number.

**FLOOR()**Â returns the largest integer less than or equal to the specified number.

**Example:**Â To round a number to two decimal places:

`SELECT ROUND(123.4567, 2) AS RoundedValue;`

**LTRIM() and RTRIM()**

**Practical Use:**Â Cleaning up strings is particularly useful when preprocessing user inputs before database insertion.

**LTRIM()**Â removes leading spaces from a string.

**RTRIM()**Â eliminates trailing spaces from a string.

**Example:**Â To trim leading and trailing spaces from a string:

`SELECT LTRIM(RTRIM(' Hello World ')) AS TrimmedString;`

Understanding scalar functions in T-SQL (Transact-SQL) is essential for manipulating and transforming data within SQL Server databases. Scalar function, functions return a single value based on the input value(s).

## Understanding Aggregate Functions

Aggregate functions in Transact-SQL (T-SQL) are powerful tools for calculating a set of values, ultimately returning a single value. These functions are particularly useful in data analysis, where summarizing large datasets is often required.

### COUNT

The COUNT function is used to count items in a dataset. For instance, if you're interested in knowing the total number and absolute value of orders in an Orders table, you could use:

`SELECT COUNT(*) AS TotalOrders FROM Orders;`

This function can be explored further in Microsoft's documentation.

### SUM

To calculate data values from the sum of a set of numeric values, you can use the SUM function. For example, calculating the total sales amount from an Orders table can be done with:

`SELECT SUM(TotalAmount) AS TotalSales FROM Orders;`

More details can be found on Simplilearn.

### AVG

The AVG function calculates the average value of a numeric table variable column. For example, to find out the average order value from the Orders table variable:

`SELECT AVG(TotalAmount) AS AverageOrderValue FROM Orders;`

### MIN and MAX

To find the first minimum value or maximum value in a set of values, MIN and MAX functions are used. For example, identifying the first non-null value in the smallest and largest order amounts can be achieved with:

`SELECT MIN(TotalAmount) AS SmallestOrder, MAX(TotalAmount) AS LargestOrder FROM Orders;`

These functions are explained in more detail on various platforms, including HubSpot's blog.

### GROUP BY

While not an aggregate function itself, GROUP BY is crucial when using aggregate functions to group results based on one or more columns. For instance, to calculate total sales per customer:

```
SELECT CustomerID, SUM(TotalAmount) AS TotalSales
FROM Orders
GROUP BY CustomerID;
```

This technique allows for one or more parameters and advanced functions detailed analysis of data query language and is covered in SQL tutorialsÂ and Mode's SQL tutorial.

### Example Scenario

Imagine we have an Orders table with columns OrderID, CustomerID, and TotalAmount. Given the following data:

To calculate total sales and the average sale amount:

```
-- Calculate total sales
SELECT SUM(TotalAmount) AS TotalSales FROM Orders;
-- Calculate average sale amount
SELECT AVG(TotalAmount) AS AverageSaleAmount FROM Orders;
```

And to find out how many orders each customer has made:

```
SELECT CustomerID, COUNT(OrderID) AS NumberOfOrders
FROM Orders
GROUP BY CustomerID;
```

These examples demonstrate how aggregate functions can simplify data analysis tasks, providing valuable insights quickly and efficiently.

## Window Functions for Advanced Data Analysis

Window Functions in SQL and system functions are powerful features that allow for complex calculations across sets of rows related to the current row. Unlike standard aggregation functions in sql, which collapse the rows into a single output row, window built-in built in database functions and system functions perform calculations without collapsing rows, maintaining the detail of the original table while still allowing for aggregate-type operations.

A classic use case for window functions in SQL is calculating running totals, averages, or rankings within a specific "window" of the dataset.

### Use Case: Ranking Sales Data

**Scenario:**Â Imagine you have a sales dataset for a company, and you want to rank the sales employees based on their total sales in descending order for each region.**Objective:**Â Rank employees within each region based on their TotalSales.**SQL Query with Window Function:**

```
SELECT
EmployeeID,
Region,
TotalSales,
RANK() OVER (PARTITION BY Region ORDER BY TotalSales DESC) AS SalesRank
FROM
EmployeeSales;
```

**Explanation:**

RANK() is the window or function name used here to rank the employees.

OVER clause specifies how to partition and order the rows that the window function operates on. In this case, we partition the data by Region so that the ranking is done separately for each built in functions region.

PARTITION BY Region divides the rows store data into partitions by region. For ranking purposes, each region's data is treated as a separate group.

ORDER BY TotalSales DESC orders the employees within each region based on their total sales in descending order.

## Create Function - How To Create A Table-valued Function In Microsoft SQL Server

To create a table-valued function in Microsoft SQL Server, you can follow these steps:

**Create the function**: Use the CREATE FUNCTION statement to either create function and define the function's name, parameters, and logic.

```
CREATE FUNCTION dbo.GetEmployeesByDepartment (@DepartmentName NVARCHAR(50))
RETURNS TABLE
AS
RETURN (
SELECT EmployeeID, FirstName, LastName
FROM Employees
WHERE Department = @DepartmentName
);
```

**Execute the function**: You can execute the function as if it were a table in a SELECT statement, passing parameters if required.

`SELECT * FROM dbo.GetEmployeesByDepartment('Sales');`

This will return a table with the EmployeeID, FirstName, and LastName columns for employees in the 'Sales' department.

Remember to replace 'Employees' with the name of your actual table and adjust the column names and data types as necessary. Also, make sure to grant appropriate permissions to users who need to access the above function, and the underlying tables.

## Comments