{"id":25009176,"url":"https://github.com/augustine-aj/entri-elevate-powerbi-projects","last_synced_at":"2026-01-08T07:07:38.036Z","repository":{"id":246789697,"uuid":"822196235","full_name":"augustine-aj/Entri-Elevate-PowerBI-Projects","owner":"augustine-aj","description":null,"archived":false,"fork":false,"pushed_at":"2024-07-28T02:36:16.000Z","size":1764,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-05T04:12:35.771Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/augustine-aj.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-06-30T14:50:17.000Z","updated_at":"2025-01-27T09:41:46.000Z","dependencies_parsed_at":"2024-07-06T10:46:48.854Z","dependency_job_id":null,"html_url":"https://github.com/augustine-aj/Entri-Elevate-PowerBI-Projects","commit_stats":null,"previous_names":["augustine-aj/entri-elevate-powerbi-projects"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/augustine-aj%2FEntri-Elevate-PowerBI-Projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/augustine-aj%2FEntri-Elevate-PowerBI-Projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/augustine-aj%2FEntri-Elevate-PowerBI-Projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/augustine-aj%2FEntri-Elevate-PowerBI-Projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/augustine-aj","download_url":"https://codeload.github.com/augustine-aj/Entri-Elevate-PowerBI-Projects/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246266252,"owners_count":20749754,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-02-05T04:12:38.633Z","updated_at":"2026-01-08T07:07:38.008Z","avatar_url":"https://github.com/augustine-aj.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Entri-Elevate-PowerBI-Projects\n\n# Project-1 \n\n# Financial Data Analysis\n\n## Overview\nThis project involves analyzing a sample dataset using Power BI. The goal is to demonstrate proficiency in data import, preprocessing, visualization, and insightful analysis. The final report includes interactive elements and is neatly organized for readability and aesthetics.\n\n## Dataset\nThe dataset contains sales data with the following columns:\n- Segment\n- Country\n- Product\n- Discount Band\n- Units Sold\n- Manufacturing Price\n- Sale Price\n- Gross Sales\n- Discounts\n- Sales\n- COGS (Cost of Goods Sold)\n- Profit\n- Date\n- Month Number\n- Month Name\n- Year\n\n## Steps Followed\n\n### 1. Importing and Preprocessing the Dataset\n- Imported the dataset into Power BI.\n- Checked for missing values and corrected data types.\n- Applied necessary transformations to ensure data quality.\n- Created new measures for better visualisatins.\n\n### 2. Visualizations\nThe report includes the following visuals:\n1. Cards showing Total sales, Total profits, Total units sold.\n2. Bar chart showing Total sales by Country.\n3. Line chart plotting Sales trends over time.\n4. Pie chart representing the distribution of Total sales by Product.\n5. Bar chart showing Gross sales by Segment.\n6. Bar chart showing Gross sales by Product..\n7. Gauge meter is displaying Profit margin.\n\n### 3. Interactive Elements\n- Added buttons for navigation between different report pages.\n- Drop down for choosing Country, Product, Segment.\n\n### 4. Insightful Analysis\nThe analysis revealed several key insights:\n- **Total Sales by Country**: United States of America is the top contributor, indicating key markets for the business.\n- **Sales Distribution by Product**: The Product 'Paseo' is most contributing  to total sales.\n- **Sales Trends Over Time**: Sales show a consistent upward trend with peaks in certain months(4th quarter)suggesting seasonality. The peak month is October.\n- **Gross Sales by Segment**: The Government segment drives a large portion of gross sales, indicating a major customer base.\n- **Profit Margin**: The profit margin gauge indicates healthy profitability, suggesting good cost management.\n\nFor a detailed analysis, please refer to the Insights section in the report.\n\n## Conclusion\nThis project demonstrates the effective use of Power BI for data analysis. The report provides a comprehensive overview of the dataset with interactive and neatly organized visuals.\nThe insights derived from the analysis are valuable for understanding key trends and patterns in the data.\n\n# Project-2 \n\n# Global Sales Data Report \n\n## Overview\nThis project aims to provide an interactive sales report for stakeholders using Power BI. The report includes various visualizations and filters to analyze sales data from different perspectives,\nhelping stakeholders make informed decisions based on the insights derived from the data.\n\n## Contents\n### First Page Visualizations\n\n#### Dropdown Filters\n- Pie Chart: Percentage of Sales by Ship Mode\n- Line Chart: Sum of Sales by Country, Region, Segment, Market\n- Bar Graph: Sum of Profits by Day, Month, Year\n- Cards: Total Profits and Total Sales\n\n### Second Page Visualizations\n\n- Tables: Sales by City, State, Region, Market, and Ship Mode\n- Dropdown filters\n\n## Setup Instructions\n1. Import Dataset:\n- Open Power BI Desktop.\n- Click on Get Data and select the file containing your sales dataset.\n- Load the dataset into Power BI.\n2. Data Cleaning:\n- Remove duplicate rows: Select relevant columns, go to the Home tab, and click on Remove Duplicates.\n- Handle missing values: Use the Transform Data option to fill missing values with appropriate replacements or remove rows with missing values.\n\n## Create Visualizations:\n\n1. First Page:\n\n- Dropdown Filters: Add slicers for State, Country, Region, Segment, and Market.\n- Pie Chart:\nSelect the Pie Chart icon.\nDrag Ship Mode to Legend and Sales to Values.\n- Line Chart:\nSelect the Line Chart icon.\nDrag Date to X-Axis and Sales to Y-Axis.\nUse filters to segment by Country, Region, Segment, Market.\n- Bar Graph:\nSelect the Bar Chart icon.\nDrag Date (formatted as day, month, year) to X-Axis and Profits to Y-Axis.\n- Cards:\nAdd two card visuals.\nDrag Sales to one card to display Total Sales.\nDrag Profit to another card to display Total Profits.\n\n2. Second Page:\n\n- Tables:\nAdd tables for Sales by City, State, Region, Market, and Ship Mode.\nDrag the corresponding fields (e.g., City, State, Region, Market, Ship Mode) to the Rows section.\nDrag Sales to Values.\n- Dropdown Filters: Add slicers for State, Country, Region, Segment, and Market.\nFormatting and Customization:\n\nUse the Format pane to customize visuals (e.g., data colors, labels, axis titles).\nAdjust visual interactions as needed.\n\n## Save and Publish:\n\nSave the Power BI file.\nPublish the report to the Power BI service for sharing with stakeholders.\n\n## Video Explanation\n\nA video has been prepared to walk you through the interactive sales report. The link is given below:\n\nhttps://drive.google.com/file/d/11v7cgUeBHzzUdGRJcQaJuVEW5Mdynnw4/view?usp=sharing\n\n## Conclusion\nThis interactive sales report provides a comprehensive view of the sales performance across different dimensions, helping stakeholders make data-driven decisions. For any questions or further assistance, please feel free to reach out.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faugustine-aj%2Fentri-elevate-powerbi-projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faugustine-aj%2Fentri-elevate-powerbi-projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faugustine-aj%2Fentri-elevate-powerbi-projects/lists"}