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https://github.com/ankitrai259/sales-analysis-dashboard-power-bi-
Sales Analysis Dashboard Using Power BI
https://github.com/ankitrai259/sales-analysis-dashboard-power-bi-
data-visualization datacleaning powerbidashboard
Last synced: 6 days ago
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Sales Analysis Dashboard Using Power BI
- Host: GitHub
- URL: https://github.com/ankitrai259/sales-analysis-dashboard-power-bi-
- Owner: AnkitRai259
- Created: 2024-10-08T07:52:21.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-10-18T20:02:54.000Z (28 days ago)
- Last Synced: 2024-10-23T02:19:39.449Z (23 days ago)
- Topics: data-visualization, datacleaning, powerbidashboard
- Homepage:
- Size: 16.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Sales Data Analysis Dashboard
# Overview
This repository contains a Sales Data Analysis Dashboard created using Power BI. The dashboard provides insights into sales performance, and product trends, enabling businesses to make informed decisions based on data-driven insights
# Dataset
The dataset used for this project is sourced from Kaggle. It includes comprehensive sales data, covering various aspects such as:
* OrderID
* ProductsName
* Region
* Quantity
* Price
* OrderDate
# Data Tranformation and Cleaning
Before creating the dashboard, the dataset was transformed and cleaned to ensure accuracy and usability. The following steps were performed:
1. Data Import: Loaded the dataset into a Pandas DataFrame.
2. Missing Values: Identified and handled missing values.
3. Data Types: Converted data types for consistency (e.g., dates, categories).
4. Outliers: Analyzed and addressed outliers that could skew analysis.
5. Aggregation: Aggregated data to derive meaningful insights (e.g., total sales by region).
6. Export: Saved the cleaned dataset for use in Power BI.
# Power BI Dashboard
The Power BI dashboard visualizes key metrics and trends derived from the sales data. Key features include:
* Interactive charts and graphs to visualize sales over time
* Customer segmentation analysis
* Product performance comparison
* Filters to drill down into specific regions or time periods
# Dashboard
