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Mohammad Taha

Data Analyst/ BI Analyst

[email protected]

Hello, I am

Mohammad Taha.

2

Excel Projects

2

PowerBI Projects

1

SQL Project

1

Python Project

About Me

A data-driven problem solver with formal education in data analytics and hands-on experience working with raw datasets to derive actionable insights. I have developed strong proficiency in key tools of the data analytics domain, including Excel, SQL, Power BI, and Python enabling me to perform data cleaning, visualization, descriptive and diagnostic analysis, transforming data findings into strategic recommendations. I am now eager to contribute to data-driven decision-making as I take on new role in the domain.

Key Skills

SQL

Python

Business Reporting

Data Storytelling

Dashboarding

Power BI

My Projects

Awards & Certificate

Excel: Mother of Business Intelligence

Get Job Ready: Power BI Data Analytics for All Levels 4.0

Data Analytics Bootcamp

Data Analytics Bootcamp

Data Science & Machine Learning

Data Science & Machine Learning

SQL for Data Analysis: Advanced SQL Querying Techniques

SQL for Data Analysis: Advanced SQL Querying Techniques

Microsoft Excel: Advanced Dashboard Design

Microsoft Excel: Advanced Dashboard Design

Microsoft Excel: Business Intelligence w/ Power Query & DAX

Microsoft Excel: Business Intelligence w/ Power Query & DAX

Microsoft Excel: Essential Statistics for Data Analysis

Microsoft Excel: Essential Statistics for Data Analysis

Power BI for Business Intelligence

Power BI for Business Intelligence

Let's Connect

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

[email protected]

https://www.linkedin.com/in/mohammadtaha-dataanalyst/

https://github.com/M-Taha-98

PowerBI Project

Customer Shopping Trends Analysis

Domain/Function: Retail

The management at retail chain is looking to use their customer purchase information to understand purchase patterns, analyze customer segments, and create a targeted marketing strategy for the upcoming season.

View Project
on GitHUB

Customer Shopping Trends Analysis

Dashboard Snapshot 1

Customer Shopping Trends Analysis

Dashboard Snapshot 2

Project Details

The project is undertaken to analyze this dataset, generate meaningful business insights and prepare a stakeholder dashboard to present the findings effectively.

The analysis step is divided into three separate business domains: Customer Demographics Analysis, Product and Category Analysis, and Geographical Analysis.

Customer Demographics Analysis:
- Age distribution of the customer base.
- Age group showing the highest loyalty measured by total previous purchases, and making the most high-value purchases.
- Purchase frequency variation across genders

Product and Category Analysis:
- Identifying product categories bringing in the highest revenue.
- Seasonal Trends: Analyze the purchase trends by season to see which seasons have the highest spending

Geographical Analysis:
- Location-Based Analysis: Mapping of areas with purchase amount to highlight areas with highest sales.
- Analyzing the preference of different shipping modes areas bringing in the most business.

Live Interactive Dashboard

Python Project

Superstore Sales And Profitability Analysis

Domain/Function: Ecommerce

The exploration of retail superstore chain's sales performance and overall profitability. Comprehensive project including data wrangling, exploratory analysis and business recommendations.

View Project
on GitHUB

View Project
on Kaggle

Superstore Sales And Profitability Analysis

Time-based trends in category level performance

Superstore Sales And Profitability Analysis

How does discount level affect profitability across different categories?

Project Details

The management team at a retail superstore chain is seeking a deeper understanding of its sales performance. This project investigates the impact of product categories, geographic regions, customer segments, and discounting strategies on overall profitability and performance.

Few of the dimensions and relationships explored are:

- Which product categories and sub-categories are leading in revenue generation and those performing poorly.
- Impact of discount variability on margins across different product categories, and identifying profitable discount thresholds.
- Time series analysis: time-based trends in category level performance.

The insights are presented for key business areas including:

- Seasonal Trend
- Overall Product Performance
- Product Portfolio Analysis and more

Based on the analysis, tailored actionable business recommendations are categorized as follows:

- Product Strategy
- Regional Customer Growth and Retention
- Discount Optimization

PowerBI Project

Performance Audit: Scaling Influencer Commerce

Domain/Function: Ecommerce/Retail

Designed to synthesize sales data into actionable plan, a high-fidelity look at 365 Retail’s inaugural year, a premium lifestyle brand for a prominent social media influencer. Identifying regional growth levers and operational friction points for better brand positioning.

View Project
Engagement

View Project
on GitHUB

Performance Audit: Scaling Influencer Commerce

Sales Analysis View

Performance Audit: Scaling Influencer Commerce

Market Analysis View

Project Details

365 Retail, features a diverse portfolio spanning apparel, gifting, and bespoke customized goods. This comprehensive performance audit seeks to synthesize sales data, consumer behavior patterns, and emerging business trends to identify critical drivers of commercial success and refine the brand’s global market positioning.

Sales Trends: Evaluation of historical sales patterns, focusing on high-level KPIs: Revenue, Average Order Value (AOV) and Average Customer Rating.

Product Level Performance: Analysis of product verticals, their performance over time and identification of best sellers and those lacking.

Market Performance: An evaluation of metrics: Sales, Units Sold, AOV across regions, comparison of local vs international regional business performance.

Customer Ratings : Assessment of customer feedback across different markets and products, impact on revenue and transactions, identification of common bottlenecks in performance driving poor ratings.

Live Interactive Dashboard

SQL Project

eCommerce Web Analytics using Advanced SQL

Domain/Function: Web Analytics

The project undertakes analysis and optimization of website traffic, marketing channels, user behavior and product portfolio for an eCommerce retailer startup.

View Project
Engagement

View Project
on GitHUB

eCommerce Web Analytics using Advanced SQL

Presentation Snapshot

eCommerce Web Analytics using Advanced SQL

Report Snapshot

Project Details

As an eCommerce Database Analyst my job is to work alongside management including the CEO, the Head of Marketing, and the Website Manager to help steer the business.

The project follows analysis and optimization of marketing channels, measuring and testing website conversion performance, and using data to understand the impact of new product launches as the business grows.

Project Breakdown
🔹 1. Traffic Source Analysis
🔹 2. Website Performance Analysis
🔹 3. Channel Portfolio Analysis
🔹 4. Product Level Analysis
🔹 5. User Level Analysis

Excel Project

Maven Careers - Exploratory Dashboard

Domain/Function: Education

This dashboard is based on a fictional company, Maven Careers, a non-profit organization helping high school seniors find career paths. The dashboard is aimed at high school students which is looking to explore wage and employment trends across industries in the US.

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Engagement

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on

Maven Careers - Exploratory Dashboard

Dashboard View

Maven Careers - Exploratory Dashboard

Dashboard View

Project Details

As the Research Analyst, I was tasked with creating a dashboard useful for high school students to explore wage and employment trends of different industries across the United States.

🛠️ Key Skills Employed:

✅ Dynamic Array Functions and Lookup Formulas
✅ Interactive Customized Charts
✅ Contextual Presentation of Numbers
✅ Dashboard Layout inline with Common Reading Pattern
✅ Dynamic Series Highlighting
✅ Form Controls for User Interactivity

I applied several visualization and design best practices to ensure clarity and engagement:

✅ Grouped low-relevance industries into a single donut chart slice to reduce visual clutter and direct focus.
✅ Used deliberate color schemes to virtually group and connect related metrics, applying the Gestalt principle of similarity to improve visual comprehension.

These are just a few of the best practices I implemented—more are covered in the full article https://mavenanalytics.io/project/36824.

Excel Project

Maven Toys - Exploratory Dashboard

Domain/Function: Retail

This exploratory dashboard is based on a fictional company, Maven Toys, a small toy store chain in the US. As the Lead Business Intelligence Analyst for Maven Toys, I have designed this dashboard as a tool for the COO and Regional Sales Managers for their monthly performance meeting.

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Engagement

View Project
on

Maven Toys - Exploratory Dashboard

Dashboard Snapshot

Maven Toys - Exploratory Dashboard

Dashboard Snapshot

Project Details

The dashboard resolves the issue faced previously where data would be presented in different formats making it difficult to follow, providing a shared unified tool which can be updated as new monthly sales data comes in.

🛠️ Key Skills Employed
✅Dynamic Array & Lookup Formulas: Leveraged FILTER, SORT, and VLOOKUP to create live summary tables
✅Customized Charts & Conditional Formatting: Use of pre-attentive attributes like size and color to highlight key data points
✅Dynamic Ranking: Used RANK and supporting formulas to automatically highlight top and bottom-performing products

📈 Dashboard Highlights
➡️Interactive trend lines tracking MoM growth
➡️Store performance comparison visualized in a sorted bar chart
➡️Matrix for granular product performance breakdown

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