End to end project on sql for business analysts

End to End Project on SQL for

Business Analysts

Diwakar Singh

Project Name: Online Shopping Platform – Customer

Order and Inventory Management System

Objective: Develop an enhanced Customer Order and

Inventory Management System to streamline order tracking, manage product inventory efficiently, and improve the overall customer experience

Justification: The existing order management system

of the eCommerce platform had issues like inventory mismatches, delays in order processing, and a lack of real-time reporting, causing customer dissatisfaction and operational inefficiencies

Business Problem: The business faced increasing

customer complaints due to inaccurate order

statuses, stockouts, and delayed order fulfillment An improved system was required to provide accurate inventory levels, better reporting on orders, and

optimized fulfillment processes

AS-IS State:

• Manual data entry for updating inventory levels

• Limited reporting on customer orders and

inventory

• Delays in updating product availability

• Disconnected systems for order tracking and

inventory

TO-BE State:

• Automated inventory updates in real-time

• Comprehensive SQL-based reporting for orders, returns, and stock levels

• Optimized product availability notifications for customers

• Integrated system connecting order management and inventory

Role Responsibl

e

Accoun table

Consul ted

r

Developers

Custom

er Support Product

Manage

r

Prioritize Features CEO

Busines

s Analyst

Customers

Develop

ers

Implementation

Lead Develop

er

Busines

s Analyst

QA Team

Scope:

• In-scope:

o Automation of inventory updates

o Real-time SQL reports on order and inventory data

o Integration of order and inventory systems

• Out-of-scope:

o Changes to payment gateway systems

Requirements:

• Business Requirements:

o Enable real-time inventory updates for the system

o Provide accurate reporting on customer

orders and inventory levels

o Allow product managers to query the system for out-of-stock notifications

o The system must send notifications when

inventory falls below a specified threshold

1 Fetching Order Data for Analysis:

As part of your role, you used SQL to analyze customer orders and generate reports for the business team Here's an example of how you queried the database

Orders Table:

CREATE TABLE Orders (

OrderID INT PRIMARY KEY,

Insert Sample Data:

INSERT INTO Orders (OrderID, CustomerID,

OrderDate, OrderStatus, TotalAmount)

VALUES

(1, 1001, '2024-01-10', 'Shipped', 150.00),

(2, 1002, '2024-01-11', 'Delivered', 250.00),

(3, 1003, '2024-01-12', 'Processing', 100.00);

SQL Query to Fetch Monthly Sales Report:

SELECT MONTH(OrderDate) AS OrderMonth,

0

This query provided monthly sales data based on delivered orders, helping the business team track performance

2 Inventory Analysis for Stock Management:

You worked closely with the inventory team to ensure real-time stock level reporting You used SQL queries

to identify low stock items and generate re-order

reports

Inventory Table:

CREATE TABLE Inventory (

ProductID INT PRIMARY KEY,

ProductName VARCHAR(50),

QuantityInStock INT,

ReorderLevel INT

);

Insert Sample Data:

INSERT INTO Inventory (ProductID, ProductName, QuantityInStock, ReorderLevel)

VALUES

(1, 'Laptop', 20, 10),

(2, 'Smartphone', 5, 15),

(3, 'Headphones', 50, 20);

SQL Query to Identify Low Stock Products:

SELECT ProductName, QuantityInStock

Smartph

This query was used to alert the inventory team when product stock was running low

3 Customer Order Status Reporting:

You created SQL reports to track the status of

customer orders and ensure smooth operations

SQL Query to Fetch Pending Orders:

SELECT OrderID, CustomerID, OrderDate

Order Date

3 1003

2024-01-12

This helped the operations team identify pending or delayed orders for faster resolution

4 Returns and Refunds Reporting:

You developed SQL queries for analyzing customer returns and refunds, contributing to a more efficient return process

Returns Table:

CREATE TABLE Returns (

ReturnID INT PRIMARY KEY,

OrderID INT,

ReturnDate DATE,

RefundAmount DECIMAL(10, 2)

);

SQL Query to Calculate Monthly Refunds:

SELECT MONTH(ReturnDate) AS ReturnMonth,

NULL NULL

In case there were returns, you would see something like:

Month

TotalRe funds

This report was used to monitor monthly refund trends and assess the financial impact of returns

5 Product Sales Insights:

You also supported the product managers by

providing detailed product performance insights using SQL

SQL Query to Fetch Top-Selling Products:

SELECT ProductID, SUM(TotalAmount) AS

Output: (assuming ProductID refers to an actual

product, adjust based on how products are defined)

ctID

Produc tSales

1 Data Integrity Risk: Potential for incorrect data in

the inventory system

a Mitigation: Implemented automated data

validation checks

2 Performance Risk: Large dataset queries could

slow down the system

a Mitigation: Optimized SQL queries for

performance

Dependencies:

• Dependence on third-party payment system

integration

• Timely data from the inventory management

software

Issues:

• Initial SQL query performance issues were

resolved through indexing and query optimization

GAP ANALYSIS

Gap Analysis Report (with SQL Integration)

Gap Identified

Steps to Cover the Gap (using SQL)

d inventory updates ensure accurate stock levels are always visible to both

customer

s and staff

Manual processes create

delays and inaccuraci

es, leading

to stockouts and poor customer experienc

e

1 Implement real-time SQL queries to update stock levels

2 Automate inventory update using SQL UPDATE queries

3 Use SQL TRIGGERS to ensure stock

is updated upon any transaction

ck = QuantityInSto

ck - 1 WHERE ProductID = 1;

Inconsiste

nt and

1 Use SQL queries to

in real time and customer

s are notified promptly

at each stage (processi

ng, shipped, delivered)

delayed status updates cause customer dissatisfaction and inefficiencies for the support team

fetch time order status

real-updates

2 Automate SQL UPDATE queries to update order statuses

dynamically

3 Implement SQL-based notifications for each

status change

WHERE OrderID = 1;

orders, sales, returns, and

refunds

The business lacks insights into sales, returns, and

customer orders due

to limited reporting capabilitie

s

1 Implement SQL SELECT queries to generate reports on orders, sales, and returns

2 Use SQL JOIN queries for complex reporting (e.g., combining

orders and inventory data)

3 Automate report

generation using SQL queries

OrderMonth, SUM(TotalAmount) AS

TotalSales FROM Orders WHERE

OrderStatus = 'Delivered' GROUP BY MONTH(OrderDate);

No proactive notificatio

1 Set up SQL TRIGGERS to monitor stock

replenishment

ns for low stock

levels lead

to stockouts, causing a loss in sales

levels and alert

managers when a product hits reorder level

2 Use SQL SELECT queries to fetch low stock products

QuantityInSto

ck FROM Inventory WHERE QuantityInSto

SQL-on returns and refunds allows for monthly analysis

of the financial impact and process

Inability to generate detailed reports on returns and refunds results in poor

financial tracking and lack

of improvement in the

1 Use SQL SELECT queries to track and analyze returns

2 Automate refund

tracking using SQL JOIN

queries between Orders and Returns tables

improve

process

es

improvement

returns process

3 Build automated SQL reports for refund analysis

1 Optimize SQL queries

system performance

ce on large datasets slows down reporting and

operation

al efficiency

with INDEXES

to improve performance

2 Regularly monitor query performance with SQL

EXPLAIN

3 Implement caching for frequent SQL reports

idx_orderdate

ON Orders (OrderDate);

y alerts, and

faster order fulfillmen

t,

Delayed order updates and

stockouts negatively affect

customer experienc

e and brand perceptio

n

1 Use SQL TRIGGERS to notify

customers of order

updates

2 Automate SQL queries for stock availability alerts

3 Improve real-time

on

customer experience with faster SQL queries for order tracking

Summary of Gaps (with SQL Integration):

1 Inventory Management Gaps: Inaccurate,

delayed manual updates leading to stockouts SQL UPDATE queries and TRIGGERS will

automate inventory updates

2 Order Tracking Gaps: Delayed order status

updates negatively affecting customer

satisfaction SQL UPDATE and TRIGGERS will provide real-time status updates

3 Reporting Gaps: Lack of robust SQL-based

reporting for orders, inventory, returns, and

refunds SQL SELECT queries and JOINS will provide comprehensive reporting

4 Product Availability Gaps: No automated

product stock notifications leading to missed

restock opportunities SQL SELECT queries and TRIGGERS will automate stock alerts

5 Return & Refund Management Gaps: Limited

insights into the returns and refunds process,

impacting financial tracking SQL SELECT and

JOIN queries will provide return and refund

reports

6 System Performance Gaps: Slow SQL query

performance on large datasets SQL INDEXES and performance monitoring with EXPLAIN will

improve speed

7 Customer Experience Gaps: Delayed updates

and stockouts leading to customer

dissatisfaction SQL TRIGGERS and automated notifications will enhance customer experience

ROOT CAUSE ANALYSIS

Problem Statement:

Customers are reporting that the system is allowing them to place orders for products that are marked as

“out of stock” in the inventory, resulting in order

cancellations and customer dissatisfaction

Root Cause Analysis:

Step 1: Investigate Inventory Management

We will begin by checking if the inventory levels are being updated correctly when orders are placed We suspect that there might be a mismatch between the available stock and the orders being placed

SQL Query: Check Stock Levels for Ordered

Products

SELECT O.OrderID, O.CustomerID, O.OrderDate, O.OrderStatus, I.ProductName, I.QuantityInStockFROM Orders O

JOIN Inventory I ON O.ProductID = I.ProductID

WHERE I.QuantityInStock = 0 AND O.OrderStatus =

e

Order Statu

s

Produ ctNa

me

Quantit yInStoc

k

101 2005

2024-01-

01

Processing

Smartphone 0

102 2006

2024-01-

02

Processing

Lapto

Root Cause Found (Step 1):

We found that orders are being processed for

products with zero stock, which indicates a failure in stock validation at the time of order placement

Step 2: Investigate Order Placement Logic

Next, we check whether there is a failure in the logic that prevents orders from being placed when the

inventory is out of stock

SQL Query: Review Orders with Invalid Stock Levels

SELECT ProductID, COUNT(OrderID) AS OrderCount, MAX(OrderDate) AS LastOrderDate

Sample Output:

Produ

ctID

OrderC ount

LastOrd erDate

2024-01-10

2024-01-09

Root Cause Found (Step 2):

The query reveals that multiple orders were placed even when the inventory level was zero, confirming that the order placement logic is not correctly

checking stock availability

Step 3: Investigate Inventory Updates After Order Placement

We will now check if the inventory is being updated correctly after an order is placed

SQL Query: Verify Inventory Update After Order

SELECT I.ProductID, I.ProductName,

I.QuantityInStock, SUM(O.TotalAmount) AS TotalSalesFROM Orders O

JOIN Inventory I ON O.ProductID = I.ProductID

WHERE O.OrderStatus = 'Delivered'

GROUP BY I.ProductID, I.ProductName,

QuantityI nStock

Total Sales

The system allowed orders to be placed for products beyond the available stock, resulting in negative stock levels This confirms a failure in the inventory update process after an order is placed

Step 4: Check SQL Triggers for Stock Updates

To understand if there is a trigger failure, we check if SQL triggers are set up correctly to update inventory after each order

SQL Query: Review SQL Triggers on Inventory

Updates

SHOW TRIGGERS LIKE 'Inventory';

Expected Output:

This query will list any triggers that are set up for

inventory updates after order placement

Sample Output:

e

Statement

Ti m in

R

Root Cause Found (Step 4):

If the output shows no triggers or incorrect triggers, this indicates that the SQL trigger is either missing or incorrectly set, causing inventory to not be updated after an order is placed

Step 5: Investigate Order Validation Logic

Finally, we check whether there is a failure in the

validation logic that prevents customers from placing orders when stock is unavailable

SQL Query: Review Order Placement Logic

SELECT O.OrderID, O.CustomerID, I.ProductID,

Produ ctID

QuantityI nStock

OrderS tatus

The system allowed orders to proceed even though the product was out of stock This confirms a flaw in the order validation logic where the system failed to check stock levels before placing the order

Root Cause Summary:

After conducting a thorough investigation using SQL queries, the root causes of the problem were

identified:

1 Stock Validation Failure: The system did not

check the available stock levels during order

placement, allowing customers to place orders for products that were out of stock

2 Trigger Misconfiguration: The SQL trigger that

should update inventory after each order was either missing or incorrectly configured, resulting

in negative stock levels

3 Order Placement Logic Flaw: The order

placement logic failed to reject orders for stock items, leading to customer dissatisfaction

out-of-Steps to Fix the Root Cause:

1 Implement Stock Validation Logic:

a Add a check in the order placement process

to verify stock levels before allowing customers to place an order

2 Fix SQL Trigger Configuration:

a Ensure that the AFTER UPDATE trigger on the Inventory table correctly updates the stock after each order

b SQL Example:

CREATE TRIGGER StockUpdate AFTER UPDATE ON Orders

FOR EACH ROW

3 Real-Time Inventory Sync:

a Implement real-time synchronization

between the inventory system and order system using SQL queries to ensure stock levels are always accurate

b SQL Example:

UPDATE Inventory

SET QuantityInStock = QuantityInStock - (SELECT

SUM(Quantity) FROM Orders WHERE ProductID =

Inventory.ProductID AND OrderStatus = 'Processing');

By fixing these root causes, the system will prevent customers from placing orders for out-of-stock items

and will maintain accurate inventory levels in real time

BUSINESS REQUIREMENT DOCUMENT

Project Name:

Online Shopping Platform – Customer Order and

Inventory Management System

Project Objective:

To develop an enhanced Customer Order and

Inventory Management System that streamlines order tracking, automates inventory management, and

provides real-time reporting to improve overall

customer experience and operational efficiency

Project Justification:

The existing system suffers from inventory

mismatches, delays in order processing, and limited reporting capabilities, leading to customer

dissatisfaction, operational inefficiencies, and

revenue loss due to stockouts and order

cancellations A new system is required to ensure

real-time inventory updates, better order

management, and improved reporting for business decisions