Solving Banking Challenges with SQL Joins and Subqueries A Practical Case Study

Note: All SQL queries used in the Case study is tested on Oracle,SQLServer,MySQL and PostgreSQL.

1.Find the customer with the highest total account balance.
SELECT c.CustomerID, c.Name, SUM(a.Balance) AS TotalBalance
FROM Customers c
JOIN Accounts a ON c.CustomerID = a.CustomerID
GROUP BY c.CustomerID, c.Name
HAVING SUM(a.Balance) = (
SELECT MAX(TotalBalance)
FROM (
SELECT SUM(Balance) AS TotalBalance
FROM Accounts
GROUP BY CustomerID
) AS Subquery
);
Explanation
It fetches the customer with maximum total account balance, taking a join between Customers and Accounts. The middle body of the query selects CustomerID, Name along with total balance for each customer by summing Balance in the Accounts table. Here, condition is needed as accounts need to be joined by its CustomerID with Customers table. So the records are grouped both for CustomerID and Name. It now means that for any customer balances of that customer can be added together. Now, for having clause to restrict the above results shows only those customers whose total balance equates to that of maximum total balance as computed in subquery. This subquery calculates the maximum total balance for that set of records-it aggregates the balances for customers and as such, it sums all the different balances and isolates the maximum total account balance that exists among all customers. The query multi-database applicable for both Oracle, MySQL, PostgreSQL and SQL Server because it follows regular SQL syntax. The outcome will provide that customer with the maximum total account balance which can perhaps be helpful for the analysis of financial statements or while setting up a customer profile.

2.Retrieve the account with the largest transaction amount.
Oracle
SELECT a.*
FROM Accounts a
WHERE a.AccountID = (
SELECT t.AccountID
FROM Transactions t
ORDER BY t.Amount DESC FETCH FIRST 1 ROW ONLY
);
Explanation
It fetches all information from the Transactions table on account with the highest amount of a transaction. It starts out by selecting all columns from the Accounts table, giving it an alias a. Then it uses the WHERE clause to limit the output only to the account whose AccountID matches the one belonging to the largest transaction. This matching AccountID is recognized by a subquery that selects AccountID of the table Transactions aliased as t. The transactions are ordered in descending manner according to the Amount column thus, the highest amount transaction will be displayed first. The FETCH FIRST 1 ROW ONLY clause limits the result of the subquery to only the top entry only, thus effectively isolation of AccountID associated with that largest transaction. Hence, the overall query will connect transaction data smoothly with account information so as to enable it to present an all-inclusive view of the account which corresponds to the highest financial activity recorded in transactions.

SQLServer
SELECT a.*
FROM Accounts a
WHERE a.AccountID = (
SELECT TOP 1 t.AccountID
FROM Transactions t
ORDER BY t.Amount DESC
);
Explanation
The SQL query returns all information about the account with the highest amount in the Transactions table. It begins with selecting all columns of the Accounts table using an alias as a.To limit the results the query has a WHERE clause applied in order to include only an account whose AccountID would be the same as that of the highest transaction amount.This can be done using a subquery that finds the first row in the Transactions table filtered to just that AccountID.It only looks at the transaction with the highest amount.The subquery orders the transactions descending by the Amount column then uses the TOP 1 clause so that only the topmost important transaction is considered for this operation.Thus the outer query actually returns the entire account information for the account pertaining to the largest transaction so that the transactions within that account can be analyzed with understanding of the related financial activity. It thus denotes a relationship between the transactions and accounts facilitating data retrieval efficiently in the context of a relational database.

______________
Mysql,PostgreSQL
______________
SELECT a.*
FROM Accounts a
WHERE a.AccountID = (
SELECT t.AccountID
FROM Transactions t
ORDER BY t.Amount DESC
LIMIT 1
);
Explanation
Returns the account that has the maximum number of transactions in particular the account with largest transaction amount in Transactions this is attained by first getting in a subquery the AccountID of the maximum Amount. What the subquery does is to give back the AccountID from table Transactions ordered in descending according to Amount so that the largest amount comes first. The clause LIMIT 1 limits the result to only the top entry which is being the AccountID having the highest transaction amount. The outer query then pulls all columns from the Accounts table where AccountID matches the result of the subquery thus effectively linking account information with the greatest transaction amount ever transacted in the Transactions table.

SQL joins with subqueries for efficient banking data retrieval and analysis

3.List customers who have no accounts.
SELECT c.CustomerID, c.Name
FROM Customers c
WHERE c.CustomerID NOT IN (
SELECT a.CustomerID
FROM Accounts a
);
Explanation
The SQL query would try to bring all those customers who, in the database, have no accounts pertaining to them. This returns CustomerID and Name from the Customers table using the alias c.
This filtering condition is done with the help of a subquery the subquery fetches the CustomerID from the Accounts table using the alias a meaning it will return all CustomerIDs that have at least one account. Now the outer query fetches for customers whose CustomerID is not in the list returned by the subquery, which effectively identifies customers with no accounts. This query will work across Oracle, MySQL, PostgreSQL and SQL Server because the syntax and logic applied will be standard SQL. The output will produce a list of customers with no linked accounts in terms of customer engagement and owning accounts within the database.

4.Get the latest transaction for each customer.
SELECT c.CustomerID, c.Name, t.TransactionID, t.Amount, t.tDate FROM Customers c
JOIN Transactions t ON c.CustomerID = t.CustomerID
WHERE t.tDate = (
SELECT MAX(t2.tDate)
FROM Transactions t2
WHERE t2.CustomerID = c.CustomerID
);
Explanation
This SQL query fetches the transaction by every customer over time. It does so by inner joining Customers with the Transactions table. SELECT statement determines which columns it will retrieve from which table namely CustomerID, Name, TransactionID, Amount and tDate respectively. The JOIN conditions are used to join the two tables together based upon the customer ID so only those transactions are included that are related to a customer. Where it uses a subquery to filter it selects all transactions whose tDate is the maximum transaction date for a given customer. This subquery will return each customer's latest transaction date that will be the largest tDate in the Transactions table but only for the row that represents the current customer being processed in the outer query WHERE t2.CustomerID = c.CustomerID. As such, this query produces the most recent transaction made by each customer in other words the most recent financial activity involving them. This is effective on all Oracle, MySQL, PostgreSQL and SQL Server platforms hence very versatile across different database settings.

Advantages of JOINS With Subqueries in SQL

1. Subqueries will break SQL queries apart they are smaller which if you will really makes a complicated query much more understandable and manageable especially in handling joins on multiple tables.
2. You can exclude certain records that you may not wish to combine in the other tables you desire using subqueries. For instance this can in some situations reduce the number of data you are working with thus it may increase the rate and efficiency of the queries.
3. Sometimes you have to apply certain conditions that depend on the result of another query. This is pretty easy with subqueries with joins helpful in managing complex data such as in banking systems where usually multiple conditions have to be met.
4. Subqueries enable dynamic data selecting in a query which can be used for real-time analysis such as getting current information in the banking transactions and then collating this data with the other relevant data that has to be analyzed.
5. Using subqueries with join you may segment and classify your data better. For example, if you're in a banking scenario you would need to analyze based on the customer or account type or transaction type hence in that process using a subquery will ease your work more.

When to Use JOINS With Subqueries ?

1. You may also utilize subqueries to create the filtering or aggregation conditions that precede the point of joining tables that may have complex relationship issues across a group of tables that hold data you want to retrieve. For example, suppose you have a banking system whereby you want to join your customer information records with actual transaction records based on given conditions.
2.Use a subquery where you need to filter or otherwise manipulate data from one table before joining it to others. That way, you can do all your preprocessing beforehand to reduce your dataset size and avoid joining unnecessary data that fills up more space in your memory than needed.
3. Joins in subqueries are great where you need to apply a rule of conditionality with complexity that is based on the requirement to compare data sets or validate, whereby conditions depend on multiple tables-something pretty handy in financial reporting once certain kinds of transactions or conditions related to accounts occur.
4. Subqueries are versatile ways of achieving summarizing data as one might when one computes total deposits or average balances before joining it with yet another table. One might be interested in fetching the total transaction amount then join it with customer details.
5. Subqueries will be most suitable when your question calls for dynamic selection of the data. They can be used in joins to retrieve current data or based on a given time frame-for example, selecting banking transactions for the last year and then joining that with customer or account information.

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