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https://github.com/bala-1409/power-bi-visualization-project

This repository contains Visualization Projects which is visualized through Power BI Software, by using the visualization we can gain multiple insights and strategies which helps to develop the business for gaining high profit margins and by the insights we can reduce the damages by accidents & calamities.
https://github.com/bala-1409/power-bi-visualization-project

dashboard data-analysis data-science data-visualization exploratory-data-analysis microsoft-excel microsoft-power-bi microsoft-powerpoint power-bi powerbi powerbi-reports powerbi-visuals visualization

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This repository contains Visualization Projects which is visualized through Power BI Software, by using the visualization we can gain multiple insights and strategies which helps to develop the business for gaining high profit margins and by the insights we can reduce the damages by accidents & calamities.

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README 

        
# _Power-BI-Visualization-Project_

_This repository contains Visualization Projects which is visualized through Power BI Software, by using the visualization we can gain multiple insights and strategies which helps to develop the business for gaining high profit margins and by the insights we can reduce the damages by accidents & calamities._

## _[Data Professional Survey Analysis](Data%20Professional%20Survey%20Analysis)_

_The dataset is the survey data of 630 Data Professionals about their Job Role, Average Salary, Job Satisfaction, etc._

  * _The data has the survey from 630 unique persons from different platforms about their Jobs, Personal Data such as Age, Gender, Ethnicity, Country._

  * _The data also has the Academic Qualifications, Salary, Working Field, etc._

  * _To verify the uniqueness one should sign in with their email but the email data is protected, it only creates virtually unique id for each unique email id._

  * _This survey was taken by the year of 2022, so the data more based on that time-period. Maybe now its slightly varies._

## _[E-Commerce Sales Analysis](E-Commerce%20Sales%20Analysis)_

_The data is from US Based E-Commerce Sales Company about their Profits and Sales Revenue._

* _The data is broken down in two different datasets, by using relationship function the both datasets can be merged with appropriate relationship between the columns of the both datasets._

* _The Primary dataset has vast data such as Customer Id & Details, Product Category & Details, Order ID & Date, Delivery Status with Shipment Details._

* _The Primary data mainly holds the measure values such as Order Quantity, Sales per order, Profit per order which gives the Overall Revenue for the Sales._

* _The Secondary data has the Geological Codes such as Latitude, Logitude, State Name & Code._

* _Create a relationship between Customer State from Primary Data and Name in Secondary Data._

## _[HR Attrition Data Analysis](HR%20Attrition%20Data%20Analysis)_

_The Reported Data collected from HR Department in a Reputed Firm which contains the Attrition Data._

* _The data is analyzed here to show various valuable insights._

* _The data has various factors such as Employee Detail, Department, Educational Qualification, Job Satisfaction Score, Working Experience at the Firm._

* _The data possess Salary Data of Each Employee, Hourly Rate, Salary Hike Percent._

* _Over-Time Working Hours, Standard Working Hours, Number of Companies Worked in Past, Total Number of Working Years can also extracted from the data._

## _[Pizza Sales Analysis](Pizza%20Sales%20Analysis)_

_The Data is from Pizza Store regarding their Sales and Revenue._

* _The Sales data is for the year of 2015 and contains 48,620 sales records._

* _The data has various factors such as pizza id, order id, pizza name id, quantity, order date, order time, unit price, total price, pizza size, pizza category, pizza ingredient and pizza name._

* _The Sales report is analysed to get further insights about sales and revenue._

* _Also, the founded insights is visualized through colourful dashboard units along with the insights statements._

## _[Road Accident Report](Road%20Accident%20Report)_

_The Data has Road Accident Report for the year 2021 and 2022 extracted from Ministry of Road Transport and Highways portal._

* _The data is analyzed to gain multiple insights which can be helpful for the Stakeholders._

* _The data insights can be used to reduce the accidents and to improve emergency rooms in hospitals based on severity._

* _The Possible Stakeholders who gain insights from the report are:_

   - _Ministry of Transport_

   - _Road Transport Department_

   - _Police Force_

   - _Emergency Services Department_

   - _Road Safety Corps_

   - _Transport Operators_

   - _Traffic Management Agencies_

   - _Public_

   - _Media_

## _[Rafik's Kitchen Data Analysis](https://github.com/bala-1409/Rafik-s-Kitchen-Data-Analysis/blob/main/Analysis%20Report/Readme.md)_

_The data is from the Fast-food Restaurant about their Sales and Expenses of the year 2022 which can be used to gain insights that helps business._

- _The collected data is of two datasets. Both the Sales and Expenses data are collected individually._

- _The Relationship is built between Sales and Expenses Data to gain proper and clear inisights for better understanding._

- _The Sales Data consists of the Sales Over a Year 2022 Except holidays which collectively has 38,157 records._

- _The Sales Data has details of Date, Order ID, Item Code, Item Name, Category, Quantity, Price, Total and Payment Mode._

- _The Expenses Data has the exact amount spend on every external expenses along with the discounts amd Store Names._

- _The Expenses Data has details of Date, Expenses Category, Amount, Discount, Final Amount after discount, Paid and Carry Forward._

- _The Sales Data helps to get clear idea about the Revenue and as far expenses data gives idea about expenses which helps to calculate profit and profit margins._