Project 2 - Supply and Demand Gap Analysis

Supply and demand gap analysis

Aim:

The aim of this project is to collect and analyze the data in detail for a cab company named as Uber_request data so that they can able to find out their Uber Pickup status point.Droping details

Introduction:

The main objective is to analyze the cab driver_id and Status of cab so that we can able to understand what Status of cabs are mostly preferred by customer by that we can introduce that Customer Status and pickup point for future so that we can be more profitable.

Problem Statements:

• In this project we have analyzed the Count of pickup point by Status.
• We have analyzed the count of Driverid in card.
• We have analyzed the Sum of Request_id by pickup point.
• We have analyzed the Driver_id.
• We have analyzed the Count of Driver id and Count of Status by pickup point.
• We have using the slicer by pickup point.
• We have analyzed the Average of request_id,Count og request timestamp .median of request_id,count of request_id and count of request_id by year.

Methodology:

Step 1:

Data Importing:

In power BI desktop with the help of the get data option, import the CSV data which is named as uber request data and click load option

Step 2:

Data Cleaning:

After loading the data and after analyzing the data I understood that there are 1316 rows and 7 columns. And in that some of the columns contained null values I have replaced the null values by 0 with the use of replace functions and started working on the data.

Step 3:

Visualizations:

In visualization part with the help of power BI desktop software I have used different kinds of charts, graphs, cards and table to display the data in the format which will be easy to understand.

Analysis:

• In this project we have analyzed the Count of pickup point by Status.
• We have analyzed the count of Driverid in card.
• We have analyzed the Sum of Request_id by pickup point.
• We have analyzed the Driver_id.
• We have analyzed the Count of Driver id and Count of Status by pickup point.
• We have using the slicer by pickup point.
• We have analyzed the Average of request_id,Count og request timestamp .median of request_id,count of request_id and count of request_id by year.

Insights:

• Here we have analyzed the average request_id and count of request id so that we able to calculate what will be sum of request id by pickup point State that the customer wants to travel and by average customer rating we can able to find our service satisfaction so that we can improve for future
• And also analyzed the pickup point by Status and trip distance according to type of cab so that we can able to understand which type of cab is preferred by people
• And also analyzed the no of customer details and cancellation details according by pickup point so that we can able to understand which cab is available for the location.

Recommendations:

• From the above analyses we can able to find that type of cab is mostly used cab by distance and it’s also highly rated by customer rating so it will be good to launch type of cabs more frequently in future so that profit will be increased
• And also we came to know that male customers uses cab services more often , so if we do advertisements more frequently means there will be chance of getting more female customers also
• And destination type is most preferred destination for that destination will increase profit.

Conclusion:

From the above analysis we are able to know that we have to do some changes for that if we follow the above recommendations by doing continuous improvisation we will more successful in future.