VickOyare/Digital-Skill-up-Africa-Project-on-Power-BI

Palmora Group HR Analysis was done in order to generate insights that can be solutions to the problem of gender inequality across the three regions/states (Kaduna, Lagos and Abuja). The analysis involve cleaning and wrangling of data, analyzing and visualization of the data in order to generate insights of what could be the solutions. # Digital-Skill-up-Africa-Project-on-Power-BI Palmora Group HR Analysis was done in order to generate insights that can be solutions to the problem of gender inequality across the three regions/states (Kaduna, Lagos and Abuja). The analysis involve cleaning and wrangling of data, analyzing and visualization of the data in order to generate insights of what could be the solutions. ## Project Topic: Palmora Data Analysis ## Project Overview: The project files are of two categories. The main file contain information such as (names, department, gender, salary, rating) while the second file contain department and rating bonus for salary improvement. The data was imported and cleaned using the Extraction, Transform and Load(ETL) method. After the cleaning, analysis and visualization of the data was done using visualization tools mostly and it is basically aimed at gender inequality. Sets of Visualization tools used are: - Clustered column chart - Question and Answer(Q&A) - Pie chart - Matrix - Addition of columns step etc. The required and expected answers were gotten and I can categorically say there is gender inequality in the company in both department and location or region in favour of the male employee ## Tools Used: Power BI: This is used for the following: - Data Collection - Data Cleaning using Extraction, Transform and Load (ETL) method. - Data manipulation - Data munching - Data Analysis - Data Visualization - Creating Report - For Presentation Tools of data visualization used are: - Clustered column chart - Question and Answer(Q&A) - Pie chart - Matrix ### Data Cleaning / Preparation: The following are steps taken when cleaning the data: - Data were extracted from the desktop into the power BI - Data were transformed and cleaned by: - Null rows were removed - Empty rows were removed - And generic gender (individual) was applied to all those without gender At this point the data is clean loaded, saved, and ready to be analyzed and visualized. ## Exploratory D …