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Mahmoud N.

@Mahmouda28

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Data Analyst

$20 USD / hora

・

Egypt (3:07 p. m.)

・

Se unió el agosto 8, 2024

$20 USD / hora

・

Dedicated Business Information Systems student with professional experience in AI training, property consultancy, and financial systems. Skilled in data analysis, business intelligence, and advanced visualization tools, with a strong foundation in technology and a commitment to continuous learning.

Verificaciones

Aceptar tarifa

100 %

Ver todo Python Developers en Egypt

Portafolio

Portafolio

12486299

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

I used Power BI and DAX to analyze and derive insights from marketing data in this project. This is Part 1 of this project, and here's a quick overview:

1️⃣ Data Preparation:

I utilized Power Query to clean and transform the raw data, ensuring it was ready for analysis.

2️⃣ Statistical Calculations and KPIs:

I applied DAX to perform various statistical calculations and generate key marketing KPIs such as CTR, Conversion Rate, and Conversion Value per Click to uncover actionable insights.

Marketing Analysis Dashboard

I used Power BI and DAX to analyze and derive insights from marketing data in this project. This is Part 1 of this project, and here's a quick overview:

1️⃣ Data Preparation:

I utilized Power Query to clean and transform the raw data, ensuring it was ready for analysis.

2️⃣ Statistical Calculations and KPIs:

I applied DAX to perform various statistical calculations and generate key marketing KPIs such as CTR, Conversion Rate, and Conversion Value per Click to uncover actionable insights.

Marketing Analysis Dashboard

12388387

Project description. Analyzing sales data (2011–2020) using Power Query and Power Pivot in Excel.

1️⃣ Data Collection and Cleaning: I imported raw sales data via Power Query, ensuring accuracy by removing duplicates, fixing errors, and standardizing data types.

2️⃣ Modeling and Analysis: Using Power Pivot, I built relationships between data tables and conducted complex calculations for deeper insights.

3️⃣ Visualizations: I created dynamic charts and pivot tables, incorporating Slicers for user-friendly filtering. This interactive dashboard provided adaptable and insightful reporting tailored to various needs.

Sales Analysis Dashboard

Project description. Analyzing sales data (2011–2020) using Power Query and Power Pivot in Excel.

1️⃣ Data Collection and Cleaning: I imported raw sales data via Power Query, ensuring accuracy by removing duplicates, fixing errors, and standardizing data types.

2️⃣ Modeling and Analysis: Using Power Pivot, I built relationships between data tables and conducted complex calculations for deeper insights.

3️⃣ Visualizations: I created dynamic charts and pivot tables, incorporating Slicers for user-friendly filtering. This interactive dashboard provided adaptable and insightful reporting tailored to various needs.

Sales Analysis Dashboard

12486299

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

In this project, I analyzed the performance of five companies by leveraging SQL for data preparation and Power BI for visualization. The goal was to unify and clean the data, generate key performance indicators (KPIs), and create interactive dashboards that provide actionable insights.

Work Completed:
1️⃣ Data Preparation (SQL)

Combined multiple datasets into a single, unified table.
Added a column to distinguish data by company name.
Ensured smooth integration of all records for a comprehensive analysis.
2️⃣ Data Cleaning & Transformation (Power Query & DAX)

Used Power Query to clean and transform raw data.
Applied DAX calculations to derive essential KPIs such as:
Total revenue
Total quantity sold
Number of brands & categories
Ensured data accuracy and consistency across all metrics.
3️⃣ Visualization & Insights (Power BI Dashboards)

Designed a comparative performance dashboard for all five companies.
Created individual dashboards for each company, showcasing:
KPI

Performance Analysis of 5 Companies

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

Project using Power BI to analyze sales data for a company from 2009 to 2012.
Data Transformation & Cleaning
I utilized Power Query to transform raw data into a clean, structured format, ensuring accuracy and readiness for analysis.

2️⃣ Advanced Calculations with DAX
Using DAX, I created dynamic measures and performed statistical calculations to reveal deeper insights into sales trends and performance metrics.

3️⃣ Interactive Dashboards
I designed multiple interactive Power BI pages, each with a unique focus:
- Main Dashboard: Highlights KPIs across four years with a slicer for year-specific analysis, dynamically impacting all other pages.
- Product Page: Examines the relationship between sales and individual products.
- Profit Page: Explores the correlation between profit and product categories.
- Regional Insights: Analyzes average delivery times, profit margins, and product diversity by region.
- Customer Segment Analysis: Maps customer segments to key performance indicators f

Data Analysis using Power BI

I used Power BI and DAX to analyze and derive insights from marketing data in this project. This is Part 1 of this project, and here's a quick overview:

1️⃣ Data Preparation:

I utilized Power Query to clean and transform the raw data, ensuring it was ready for analysis.

2️⃣ Statistical Calculations and KPIs:

I applied DAX to perform various statistical calculations and generate key marketing KPIs such as CTR, Conversion Rate, and Conversion Value per Click to uncover actionable insights.

Marketing Analysis Dashboard

I used Power BI and DAX to analyze and derive insights from marketing data in this project. This is Part 1 of this project, and here's a quick overview:

1️⃣ Data Preparation:

I utilized Power Query to clean and transform the raw data, ensuring it was ready for analysis.

2️⃣ Statistical Calculations and KPIs:

I applied DAX to perform various statistical calculations and generate key marketing KPIs such as CTR, Conversion Rate, and Conversion Value per Click to uncover actionable insights.

Marketing Analysis Dashboard

12388387

Project description. Analyzing sales data (2011–2020) using Power Query and Power Pivot in Excel.

1️⃣ Data Collection and Cleaning: I imported raw sales data via Power Query, ensuring accuracy by removing duplicates, fixing errors, and standardizing data types.

2️⃣ Modeling and Analysis: Using Power Pivot, I built relationships between data tables and conducted complex calculations for deeper insights.

3️⃣ Visualizations: I created dynamic charts and pivot tables, incorporating Slicers for user-friendly filtering. This interactive dashboard provided adaptable and insightful reporting tailored to various needs.

Sales Analysis Dashboard

Project description. Analyzing sales data (2011–2020) using Power Query and Power Pivot in Excel.

1️⃣ Data Collection and Cleaning: I imported raw sales data via Power Query, ensuring accuracy by removing duplicates, fixing errors, and standardizing data types.

2️⃣ Modeling and Analysis: Using Power Pivot, I built relationships between data tables and conducted complex calculations for deeper insights.

3️⃣ Visualizations: I created dynamic charts and pivot tables, incorporating Slicers for user-friendly filtering. This interactive dashboard provided adaptable and insightful reporting tailored to various needs.

Sales Analysis Dashboard

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Helwan University Cairo

2020 - 2024

•

4 años

3.74

Egypt

2020 - 2024

•

4 años

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