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📊 Data Analyst Portfolio

Hi, I’m Ijeoma Annie Chris 👋🏽 a Data Analyst skilled in SQL, Excel, Power BI, and Python.
This portfolio showcases real-world projects demonstrating data cleaning, analysis, visualization, and reporting.

All projects use the same dataset: sales_data.csv.

📂 Portfolio Structure

│── README.md

│── SQL/

│ └── layoffs.sql

│── Python/

│ └── EDA.ipynb

│── Excel/

│ └── Customer_Segmentation.xlsx

│── PowerBI/

│ └── Retail_Dashboard.pbix

│── Tableau/

│ └── layoffs.twbx

│── Datasets/

│ └── sales_data.csv

🔹 Projects

1. SQL: Sales_Analysis.sql

Description:
This project contains SQL queries to analyze sales data for a retail company.
Key tasks performed:

  • Total revenue and quantity sold by region
  • Top 5 best-selling products
  • Monthly sales trends by category
  • Average order value by region
  • Revenue contribution percentage of each region

Skills demonstrated: SQL aggregation, filtering, grouping, ordering, subqueries

📂 File: SQL/layoffs.sql
📂 Dataset used: Datasets/sales_data.csv


2. Python: EDA.ipynb

Description:
Exploratory Data Analysis (EDA) using Python and Pandas to extract insights from sales data.
Key tasks performed:

  • Data cleaning and preprocessing
  • Revenue analysis by region
  • Top product analysis with pie charts
  • Monthly sales trends using line charts

Skills demonstrated: Python, Pandas, Matplotlib, Seaborn, data visualization

📂 File: Python/EDA.ipynb
📂 Dataset used: Datasets/sales_data.csv


3. Excel: Customer_Segmentation.xlsx

Description:
A customer segmentation project in Excel for a retail company.
Key tasks performed:

  • Organized customer data with Total Purchases, Avg Purchase Value, and Loyalty Score
  • PivotTables to analyze revenue by region
  • Charts for customer segmentation visualization
  • Dashboard highlighting top customers and loyalty trends

Skills demonstrated: Excel, PivotTables, charts, dashboards, conditional formatting

📂 File: Excel/Customer_Segmentation.xlsx


4. Power BI: Retail_Dashboard.pbix

Description:
Interactive Power BI dashboard for retail sales analysis.
Key tasks performed:

  • Created KPIs: Total Revenue, Total Quantity, Average Order Value
  • Bar chart: Revenue by Region
  • Line chart: Monthly sales trends by category
  • Pie chart: Top 5 products by revenue
  • Slicers for filtering by Region, Category, and Date

Skills demonstrated: Power BI, data modeling, interactive dashboards, data visualization

📂 File: PowerBI/Retail_Dashboard.pbix
📂 Dataset used: Datasets/sales_data.csv


5. Dataset: sales_data.csv

Description:
Sample retail sales dataset used for all projects. Contains:

  • OrderID, Product, Category, Region, Sales, Quantity, OrderDate

📂 File: Datasets/sales_data.csv

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Data Analyst Portfolio showcasing SQL, Excel, Power BI, and Python projects.

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