Moaz Shaker

Online Superstore Performance Dashboard

The dashboard provides an overview of the performance in terms of sales and profits, as well as customer behavior insights and product trends.

The dashboard provides an overview of the performance of online Superstore in terms of sales and profits, as well as insights into customer behavior and product trends over the course of this year, including a comparison to past year results.

The dashboard consists of four pages according of what level of details we want,
📍 Executive Summary which contains different sections:
- KPIs Section: Sales Performance, Profit Performance, Orders and Customers count . Each section provides detailed information about the store's performance in that area. It also shows how every section has changed over time and in comparison to last year so we can detect seasonal trends for each product as well as overall trends in their volume over time.

🔗 I made sure The KPIs filter is user-friendly so you can filter the whole dashboard easily just by clicking over "Sales – Profit – Orders".

- Then provides a breakdown of KPIs by segment, product category and subcategory, It also includes charts showing the top 5 Manufacturers selling products and also how each month performance compares to the previous year's performance. " ⚪ for PY and 🔴 for CY"

- Top returned products which helps in identifying quality issues so we can send feedback to the quality management team. - You can also breakdown by region and there's a small map to breakdown by state but If you want to compare locations performance you can click on "Full Map Icon".

📍 Transaction Details
You can see the Transaction details just by clicking on "Order Details Icon" which provides detailed information containing Order ID, Transaction date, Customer name, Address, Is the order profitable or not, shipment method and finally the order status(Completed or still Pending).

📍 Full Map
Overall, this dashboard provides a comprehensive overview of the Superstore's performance across multiple areas, allowing C-level executives to quickly identify areas where performance can be improved or capitalized upon.

📍 Customers LTV
Just small chart of customer LTV over the past 4 years broken down by successive 16 quarters. It is an important metric for businesses because they can make more informed decisions about how much to invest in acquiring new customers, how much to spend on retaining existing customers, and how much revenue they can expect to generate from each customer over time.

Check project on GitHub.

Data Modeling and
BI-Optimized Cleaning.

I experimented with both star and snowflake schemas to effectively structure and organize the data of firms selling computer workstations. Additionally, I also performed data cleaning tasks to ensure the data's optimal usability within BI tools.

Emergency Room Admission Dashboard

Designed to help healthcare professionals understand and analyze emergency room admission trends in order to be ready to save more lives!

ETL-Data-Pipeline-using-AirFlow

End-to-end ETL pipeline using Apache Airflow. Extracts sales data from PostgreSQL, transforms with Python (pandas), aggregates daily revenue, and generates a time-series visualization — a strong portfolio project for data engineering workflows.

This project demonstrates an end-to-end automated ETL pipeline built with Apache Airflow. It extracts sales data from a PostgreSQL database, transforms it using Python (pandas), and calculates total revenue per day. The pipeline also generates a time series visualization of revenue trends, making it a strong portfolio project for data engineering and analytics workflows.

✨ Features

Extract: Query order and product data from PostgreSQL
Transform: Clean, join, and aggregate daily revenue with pandas
Load: Save results as CSV and PNG outputs
Schedule: Automated daily execution with Airflow
Visualize: Daily revenue plot for trend analysis

📂 Project Structure

total_revenue_pipeline/
├── dags/
│   └── sales_revenue_dag.py
├── data/
│   └── RetailDB_postgres.sql
├── outputs/
│   ├── daily_sales_data.csv
│   ├── daily_revenue.csv
│   └── daily_revenue_plot.png
└── README.md

⚙️ Workflow (Airflow DAG)

Extract Data — Join orders, order_details, and products
Transform Data — Compute total and average revenue per day
Load & Visualize — Write CSV outputs and a line plot

🛠 Tools & Tech

Apache Airflow — orchestration
PostgreSQL — source database
Python (pandas, matplotlib) — transformation & visualization

Explore the repository on GitHub

Airlines Delayed

Comprehensive analysis of U.S. airline delays in 2008 using Power BI. Explores ~2M flight records to uncover trends, causes of delays, cancellations, and diversions. Interactive dashboards surface actionable insights for improving airline operations and passenger experience.

This project presents a comprehensive analysis of U.S. airline delays in the year 2008. Using Power BI, it explores ~2M flight records to identify trends and the primary causes of delays, cancellations, and diversions.

🎯 Objectives

Visualize and analyze large-scale flight delay data for 2008
Identify frequent causes of delays and cancellations
Understand patterns across time, carriers, and airports
Deliver interactive dashboards for actionable insights

🛠 Tools

Power BI Desktop (visualization & modeling)
Power Query (data cleaning & transformation)
DAX (calculated measures and KPIs)

📊 Dashboard Pages

General Analysis — KPIs, monthly trends, airline comparisons, geography
Cancellation & Diversion Analysis — root causes and distributions
Delay Analysis — average delay time by cause, patterns by airline/airport/day

Explore the repository on GitHub

League of Legends Analytics

Excel and Power BI exploration of League of Legends data. Cleaned and transformed with Power Query, modeled with DAX, and built into an interactive dashboard for role performance and champion insights.

HR Attrition Analytics

A Power BI project for HR departments, utilizing Power Query, DAX, interactive filters, and drill-through features to analyze employee attrition and provide actionable insights.

Checking In, Checking Out

People tend to leave bad reviews on various hotels due to minor details, and I believe those small details can affect the whole guest experience, so let's take a look !

Hotel Booking Analysis Report

The dashboard is designed to help hotel managers and administrators understand and analyze booking trends and patterns.

-The Hotel Booking Analysis report is a visual representation of hotel booking data. - On Top there's a quick overview of the total number of Bookings, Total Revenue generated, Reservation Status, Number of Guests and their average stay Period.

-Then the Booking Channels section provides information on the number of bookings by booking channel, which can help hotel managers determine the effectiveness of their marketing strategies and adjust their focus accordingly.

-The Guest Preferences section provides information on the percentage of bookings by room type, such as single, double, Queen, Suite, etc. This information can help hotel managers identify their target audience and tailor their marketing efforts accordingly.

I prefer this project to be called a report more than interactive dashboard but you can filter the data to choose the month you need or If you want to compare properties using the two drop down lists on Top of the Dashboard "The Default Numbers shown represents all Properties and all months."

The hotel transactional page is designed for managing and your reservations effectively. It allows you to have a detailed view of the reservations, and make informed decisions to optimize the hotel's operations. And It contains:

1. Total Guests: It includes both adults and children to give you an idea of the occupancy level for each booking.
2. Booking Channel: This column specifies the channel through which the reservation was made. 3. Room Type: This column provides information about the type of room booked for each reservation. It may include options such as standard rooms, deluxe rooms, suites.
4. Cost: The cost column indicates the price associated with each reservation. It includes the total amount the guest is expected to pay for their stay, including any additional charges or fees.
5. Status: This column displays the current status of the reservation. It helps you track whether a reservation has been completed, marked as a no-show, extended, or reduced. This information allows you to manage inventory and make informed decisions regarding room availability.

Please note that this report aims to provide an overview of the reservation details. For more detailed information or specific analytics, further analysis can be conducted based on the data collected in the dashboard.

Check project on Tableau.

Product Survey Responses Analysis

Multiple versions of Analysis of product survey with recommendations.
1) Diverging version.
2) Stacked bar version.
3) Multiple bar version.

In this Project I dealt with unstructured data, positive & negative sentiment and "floating" bar charts. It's got a little bit of everything. You can go through images to see the three versions:
1) Diverging version.
2) Stacked bar version.
3) Multiple bar version.
Don't forget to tell me which version is more aesthetics.

- Results and Recommendations:
1- The results of the survey showed that the product was recognized by customers as being durable, suitably priced, and intuitive to use. So The advertising team should focus on their campaign on highlighting those aspects.
2- Customers were more neutral or sometimes angry on the aesthetics form, finish, and materials used, there were also overall negative responses on affordability and how easy it was to use the product.

- So despite the positive findings related to price and durability, we should form feedback to our design and quality management teams.
For the whole story on Tableau : Click here

Reduce Marketing Budget for Travel Insurance company

I was an analyst for Travel Assured which is a travel insurance company. They have had to cut their marketing budget by over 50 % due to covid-19 pandemic. So It is more important now than ever that they advertise in the right places and to the right people .

ABOUT ME

What I
Can Offer

Reporting and Dashboard Creation

Data Management

Analysis and Interpretation

Working with these tools brings me joy

Results-Driven
Project Samples

Online Superstore Performance Dashboard

Data Modeling and
BI-Optimized Cleaning.

Emergency Room Admission Dashboard

ETL-Data-Pipeline-using-AirFlow

Airlines Delayed

League of Legends Analytics

HR Attrition Analytics

Checking In, Checking Out

Hotel Booking Analysis Report

Product Survey Responses Analysis

Reduce Marketing Budget for Travel Insurance company

Online Superstore Performance Dashboard

Data Modeling and
BI-Optimized Cleaning

Hotel Booking Analysis Report

Reduce Marketing Budget for Travel Insurance company

Product Survey Responses Analysis

Emergency Room Admission Dashboard

Video Game Sales Analysis (SQL)

A Detailed Analysis of Las Vegas Hotels Reviews - Python Project

Optimizing online sports retail revenue - SQL Project

Let's Work
Together

GET IN TOUCH

ABOUT ME

What I Can Offer

Reporting and Dashboard Creation

Data Management

Analysis and Interpretation

Working with these tools brings me joy

Results-Driven Project Samples

Online Superstore Performance Dashboard

Data Modeling and BI-Optimized Cleaning.

Emergency Room Admission Dashboard

ETL-Data-Pipeline-using-AirFlow

Airlines Delayed

League of Legends Analytics

HR Attrition Analytics

Checking In, Checking Out

Hotel Booking Analysis Report

Product Survey Responses Analysis

Reduce Marketing Budget for Travel Insurance company

Online Superstore Performance Dashboard

Data Modeling and BI-Optimized Cleaning

Hotel Booking Analysis Report

Reduce Marketing Budget for Travel Insurance company

Product Survey Responses Analysis

Emergency Room Admission Dashboard

Video Game Sales Analysis (SQL)

A Detailed Analysis of Las Vegas Hotels Reviews - Python Project

Optimizing online sports retail revenue - SQL Project

Let's Work Together

GET IN TOUCH

What I
Can Offer

Results-Driven
Project Samples

Data Modeling and
BI-Optimized Cleaning.

Data Modeling and
BI-Optimized Cleaning

Let's Work
Together