Project 2 - Supply and Demand Gap Analysis
Aim
The aim of this project is to collect and analyze the 2011 Census Data of Tamilnadu in order to know the human resource demand and supply based on their age group.
Introduction
The data is taken from the official Census website of India and chosen Tamilnadu state for analysing the Demand and supply of Human Resourse based on their age group classification.
The main objective of this project is to analyze the Census data of Tamilnadu, Through the analysis of data, we can find some important insights.
Problem Statement.
In this project, we find out, how many percentage of People working, and how many percentage of people are seeking for the Job through Employment and Unemployment ratio, Here, we analyse the each districts of the state based on their age group.
Methodology
- In Census data, the Data set shows the total population of the state including each districts population, the next columns shows main workers of the each district, Job seeking Male and female and Non working Male and female of each district.
- Based on the data of each district, I made a view of Gender Bias population ratio, Unemployement Ratio of each district.
- The data includes the Age group slab People population so each categorial analysis is included.
- The data set also provides Main workers of each district in gender wise, working community of each district is analysed.
- Another column is Status of each district's Non-Working Employee in age based sections.
- The last two column set represents the Job seeking people in both gender .
- The first step is cleaning the data. In data cleaning I cleaned the data with the transform data option present in Power BI because the dataset was not cleaned and included some missing values, so with the help of the duplicates function in Power BI, I cleaned the data and replace the null values with 0 and then started working on it.
- After Data cleaning performs the Data interpretation step. In Data interpretation found some important information.
- The data set was almost clean and completed.
- Replace the Null values with 0
- There is a total of 1585 rows and 18 columns are present.
Visualization
In visualization, I took the help of Power BI Desktop software to make graphs and charts here some relevant graphs and charts are attached.
From the above Visualization find some interesting points that are mentioned below
- In the districts like Chennai, coimbatore, Kancheepuram the employement Ratio is higher which shows maximum Number of population in working, also the Job seeking ratio is higher.
- The overall data provides the data that age group slab 25 to 49 is maximum number of people are working.
- When comparing with Male and Female, Male has dominant in working age group between 20 to 60 years old but women age group working status is 20 to 39.
- The job seeking population is higher in Urban with the age group of 20 to 30, It shows that Urban population has more opputunities.
- The Main workers Of each district is categorised in age wise it shows the maximum Main Workers are from Urban areas the women ratio is higher when comparing with rural.
Insights
- In conclusion, we can take a look at the final Dashboard for further Analysis.
- We analyzed the data according to the Working and Non_Working Population.
Recommendations
- We can analyze the data of the overall Human resourse of the country .
- Like this dataset, we can Analyze the Data according to the Different Cities-Area it takes more clarity to how to fill the supply and demand gap
- We can analyze the data with the proper format
- We can collect good datasets for more effective analysis by using charts.
Conclusion
In Conclusion, we can take look at the Dashboard for further Analysis.
- According to analysis, almost the Urban area is having More Job working person when compared with rural, the women workers is having large numbers in Urban areas.
- The age group between 20 to 30 years of age is mostly Job seeking in state so special employent drive can be intiated by government.