تصميم Dashboard احترافية لتحليل بيانات المبيعات باستخدام Excel و Power BI

This project focuses on collecting, cleaning, and analyzing large datasets to extract meaningful insights that can support decision-making and strategic planning. The project workflow includes the following stages: Data Collection: Gathering structured and unstructured data from multiple sources such as databases, CSV/Excel files, APIs, or web scraping. Data Cleaning & Preprocessing: Handling missing values, duplicates, inconsistencies, and formatting issues. Transforming raw data into a consistent and usable format for analysis. Exploratory Data Analysis (EDA): Using statistical methods and visualizations (like histograms, scatter plots, and box plots) to understand data distribution, detect trends, identify outliers, and reveal relationships between variables. Statistical Analysis & Modeling: Applying descriptive statistics, correlation analysis, hypothesis testing, and predictive modeling techniques such as regression, classification, or clustering to uncover patterns and forecast trends. Data Visualization: Creating dashboards and interactive visualizations to present findings clearly using tools like Matplotlib, Seaborn, Tableau, or Power BI. Insights & Recommendations: Summarizing actionable insights that help businesses or researchers make data-driven decisions, optimize processes, and improve outcomes. Technologies & Tools Used: Python (Pandas, NumPy, Matplotlib, Seaborn), SQL, Excel, Tableau/Power BI, and optionally machine learning libraries like Scikit-learn.