B. Customer Transactions.md

B. Customer Transactions

1. What is the unique count and total amount for each transaction type?

SELECT
	txn_type,
    COUNT(customer_id) AS number_of_customers,
    SUM(txn_amount) AS total_amount
FROM
	customer_transactions
GROUP BY 
	txn_type;

Output:

txn_type	number_of_customers	total_amount
deposit	2671	1359168
withdrawal	1580	793003
purchase	1617	806537

2. What is the average total historical deposit counts and amounts for all customers?

SELECT
    txn_type,
    AVG(deposit_count) AS average_deposit_count,
    AVG(deposit_amount) AS average_deposit_amount
FROM (
	SELECT 
		customer_id,
		txn_type,
		COUNT(*) AS deposit_count,
		SUM(txn_amount) AS deposit_amount
	FROM 
		customer_transactions
	WHERE
		txn_type = 'deposit'
	GROUP BY
		customer_id, txn_type
        ) deposits
GROUP BY
	txn_type;

Output:

txn_type	average_deposit_count	average_deposit_amount
deposit	5.3420	2718.3360

3. For each month - how many Data Bank customers make more than 1 deposit and either 1 purchase or 1 withdrawal in a single month?

WITH TransactionsCount AS ( -- It is counting the number of transactions made my each customer per month for each category
    SELECT
        customer_id,
        DATE_FORMAT(txn_date, '%Y-%m') AS txn_month,
        COUNT(CASE WHEN txn_type = 'deposit' THEN 1 END) AS deposit_count,
        COUNT(CASE WHEN txn_type = 'purchase' THEN 1 END) AS purchase_count,
        COUNT(CASE WHEN txn_type = 'withdrawal' THEN 1 END) AS withdrawal_count
    FROM 
        customer_transactions
    GROUP BY
        customer_id,
        DATE_FORMAT(txn_date, '%Y-%m')
	 ORDER BY
		customer_id ASC
)
SELECT 
    txn_month,
    COUNT(customer_id) AS customers_meeting_criteria
FROM
    TransactionsCount
WHERE 
    deposit_count > 1 AND (purchase_count >= 1 OR withdrawal_count >= 1) -- counting customers who made more than one deposit and at least one purchase or at least one withdrawal in a single month.
GROUP BY
    txn_month
ORDER BY
    txn_month ASC;

Output:

txn_month	customers_meeting_criteria
2020-01	168
2020-02	181
2020-03	192
2020-04	70

4. What is the closing balance for each customer at the end of the month?

WITH impact AS ( -- It is factoring in the impact of purchase, withdrawal and deposit
	SELECT
		customer_id,
		DATE_FORMAT(txn_date, '%Y-%m') AS txn_month,
		CASE
			WHEN txn_type = 'deposit' THEN txn_amount 
            ELSE txn_amount * -1 
            END AS impact_of_transactions
	FROM
		customer_transactions
	GROUP BY
		customer_id,
		DATE_FORMAT(txn_date, '%Y-%m'),
        impact_of_transactions
	ORDER BY customer_id ASC
    ),
MonthlyTotal AS ( -- It is calculating the total balance per month
	SELECT 
		customer_id,
		txn_month,
		SUM(impact_of_transactions) AS total_balance
	FROM
		impact
	GROUP BY
		customer_id,
		txn_month
	ORDER BY customer_id ASC
		)
SELECT
	customer_id,
	txn_month,
    SUM(total_balance) OVER (PARTITION BY customer_id ORDER BY txn_month ASC) AS closing_balance
FROM
	MonthlyTotal;

Output:

customer_id	txn_month	closing_balance
1	2020-01	312
1	2020-03	-640
2	2020-01	549
2	2020-03	610
3	2020-01	144
3	2020-02	-821
3	2020-03	-1222
3	2020-04	-729

Please note that this output is limited to save the space. 5. What is the percentage of customers who increase their closing balance by more than 5%?

WITH impact AS ( -- It is factoring in the impact of purchase, withdrawal and deposit
	SELECT
		customer_id,
		DATE_FORMAT(txn_date, '%Y-%m') AS txn_month,
		CASE
			WHEN txn_type = 'deposit' THEN txn_amount 
            ELSE txn_amount * -1 
            END AS impact_of_transactions
	FROM
		customer_transactions
	GROUP BY
		customer_id,
		DATE_FORMAT(txn_date, '%Y-%m'),
        impact_of_transactions
	ORDER BY customer_id ASC
    ),
MonthlyTotal AS ( -- It is calculating the total balance per month
	SELECT 
		customer_id,
		txn_month,
		SUM(impact_of_transactions) AS total_balance
	FROM
		impact
	GROUP BY
		customer_id,
		txn_month
	ORDER BY customer_id ASC
		),
ClosingBalance AS ( -- It is calculating closing balance
	SELECT
		customer_id,
		txn_month,
		SUM(total_balance) OVER (PARTITION BY customer_id ORDER BY txn_month ASC) AS closing_balance
	FROM
		MonthlyTotal
    ),
PreviousMonthClosing AS ( -- It is calculating the closing balance for previous month
    SELECT
        customer_id,
        txn_month,
        closing_balance,
        LAG(closing_balance, 1) OVER (PARTITION BY customer_id ORDER BY txn_month) AS last_month_closing_balance
    FROM
        ClosingBalance
),
PercentageIncrease AS (
	SELECT
		customer_id,
		txn_month,
		closing_balance,
		last_month_closing_balance,
		CASE
			WHEN last_month_closing_balance IS NULL OR last_month_closing_balance = 0 THEN NULL
			ELSE (closing_balance - last_month_closing_balance) / last_month_closing_balance * 100
		END AS percentage_increase
	FROM
		PreviousMonthClosing
	)
SELECT 
    ROUND(COUNT(DISTINCT customer_id) / (SELECT (COUNT(DISTINCT customer_id)) FROM customer_transactions) * 100, 2) AS percentage_of_customers
FROM
	PercentageIncrease
WHERE 
percentage_increase >= 5.00;

Output:

percentage_of_customers
76