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an end-to-end sales data dashboard that integrates data from multiple sources to provide insights on sell-in and sell-out metrics, customer behavior, and sales performance trends.

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minhajbinhafsahnazer/Comprehensive-Sales-Data-Analysis-and-Dashboard

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Comprehensive Sales Data Analysis and Dashboard 📊

Objective 🎯

The goal of this project is to build an end-to-end sales data dashboard that integrates data from multiple sources to provide insights on sell-in and sell-out metrics, customer behavior, and sales performance trends.

Data Used 📦

This project leverages sales data from Amazon Sales Data 2023, covering the following categories:

  • Beauty and Grooming
  • Furniture Sales
  • Health and Personal Care
  • Home Decor

The data includes product details, pricing, ratings, discounts, and customer behavior metrics, offering a rich foundation for analysis and actionable insights.

Scope 🔍

  • Data Cleaning & Preparation 🧹: The sales data is sourced from multiple locations (e.g., Excel, SQL databases). Initial cleaning and preparation are performed to ensure data integrity.
  • Exploratory Data Analysis (EDA) 🔬: EDA is conducted to identify patterns in the data, uncover key metrics, and highlight trends that will be useful for business stakeholders.
  • Dashboard Development 📈: A dashboard is created using Power BI or Tableau to display actionable insights such as:
    • Top-selling products 🏆
    • Customer behavior trends 📅
    • Regional sales performance 🌍
    • Key performance indicators (KPIs) 📊

Skills Demonstrated 💡

  • Data Cleaning & Preparation 🧹: Handling messy data, removing duplicates, handling missing values, and standardizing data formats.
  • Exploratory Data Analysis (EDA) 🔍: Using statistical techniques to uncover patterns, trends, and insights in the sales data.
  • Data Visualization 🖼️: Creating intuitive and interactive dashboards to present insights clearly to cross-functional teams.
  • Cross-Functional Reporting 📣: Communicating results effectively to stakeholders with varying levels of data expertise.

Tools ⚙️

  • SQL 🗄️: Used for querying data from databases and performing aggregation and joins.
  • Power BI / Tableau 📊: Data visualization tools used to create dynamic, interactive dashboards for end users.
  • Python 🐍: Leveraged for data cleaning, exploratory analysis, and handling large datasets. Libraries such as Pandas, NumPy, and Matplotlib are used.
  • Excel 📉: Initial data processing and organization before importing data into more advanced tools for analysis.

Why It Fits ✅

This project is ideal for gaining hands-on experience in business intelligence and data analysis. It focuses on solving real-world business problems around customer behavior, sales trends, and performance tracking. The skills demonstrated are applicable to roles such as:

  • Data Analyst 📊
  • Business Intelligence Analyst 📈
  • Data Engineer 🛠️

the project provides actionable insights and fosters data-driven decision-making for businesses. 🚀

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an end-to-end sales data dashboard that integrates data from multiple sources to provide insights on sell-in and sell-out metrics, customer behavior, and sales performance trends.

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