Understanding the SQL Query for Counting Unknown and Known Customers

As a technical blogger, it’s essential to delve into the intricacies of SQL queries that can help extract valuable insights from databases. In this article, we’ll explore how to use a SQL query to count all customers, unknown customers, and known customers based on their phonemacaddress column.

Understanding the Table Structure

To grasp the problem at hand, let’s first examine the table structure:

The phonemacaddress column is used to identify customers uniquely. The IsKnownCustomer column contains a boolean value indicating whether the customer is known or unknown.

Understanding the Problem

We’re tasked with writing a SQL query that can count all customers, unknown customers, and known customers based on their phonemacaddress column.

Approach: Using GROUPING and CASE Statements

To achieve this, we’ll employ two essential SQL techniques:

1. GROUP BY: This clause groups the records in the table by a specified column or expression.
2. CASE Statement: This statement allows us to perform conditional logic within a SELECT query.

Here’s how we can use these techniques together to write our SQL query:

SELECT 
    COUNT(DISTINCT phonemacaddress) [count Customer] , 
    CASE 
        WHEN GROUPING(IsKnownCustomer) = 1 THEN 'all' 
        WHEN IsKnownCustomer = 1 THEN 'known customer' 
        WHEN IsKnownCustomer = 0 THEN 'unknown customer' END [customer type] 
FROM @CustomerTable
GROUP BY IsKnownCustomer WITH ROLLUP
ORDER BY GROUPING(IsKnownCustomer) DESC, IsKnownCustomer 

How the Query Works

Let’s break down how this query works:

• The SELECT clause specifies that we want to count the distinct occurrences of each customer’s phonemacaddress. We use the COUNT(DISTINCT) function to achieve this.
• The CASE Statement allows us to perform conditional logic within our SELECT query. It checks the value of IsKnownCustomer and assigns a label accordingly:
  • If GROUPING(IsKnownCustomer) = 1, it means that we’re grouping by all unique values in the phonemacaddress column, so we assign 'all' to the customer type.
  • If IsKnownCustomer = 1, it means that we’ve grouped by known customers, so we assign 'known customer'. Otherwise, if IsKnownCustomer = 0, we assign 'unknown customer'.
• The GROUP BY clause groups the records in the table by the value of IsKnownCustomer. We use the WITH ROLLUP option to include aggregate values for each group (i.e., the total count of customers, unknown customers, and known customers).
• Finally, we sort the results based on whether grouping was performed (GROUPING(IsKnownCustomer)) in descending order. This ensures that the “all” category is displayed first.

Handling NULL Values

To accurately count all customers, including those with missing phonemacaddress values (NULL), we need to handle these cases separately:

SELECT 
    COUNT(DISTINCT CASE WHEN phonemacaddress IS NOT NULL THEN phonemacaddress ELSE 'Unknown' END) [count Customer] , 
    CASE 
        WHEN GROUPING(IsKnownCustomer) = 1 THEN 'all' 
        WHEN IsKnownCustomer = 1 THEN 'known customer' 
        WHEN IsKnownCustomer = 0 THEN 'unknown customer' END [customer type] 
FROM @CustomerTable
GROUP BY IsKnownCustomer WITH ROLLUP
ORDER BY GROUPING(IsKnownCustomer) DESC, IsKnownCustomer 

In this modified query:

• We use a CASE statement within the COUNT(DISTINCT) function to count only non-NULL values for phonemacaddress. If the value is NULL, it defaults to 'Unknown'.
• The rest of the query remains unchanged.

Example Results

The final output will look like this:

In this example, we have a total of 14 customers: 7 with unique phonemacaddress values, 3 who are unknown customers (i.e., their IsKnownCustomer value is 0), and 4 known customers (i.e., their IsKnownCustomer value is 1).

Conclusion

In this article, we’ve explored how to write a SQL query that can count all customers, unknown customers, and known customers based on their phonemacaddress column. By leveraging the GROUP BY clause and CASE statement, we were able to accurately identify these categories.

Last modified on 2023-08-10