Aim:

The objective is to identify and analyze the problems in Supply-Demand of Uber trips from City to Airport and vice-versa across various hours of the day and find out possible solutions to address the problem.

Problem Statement:

Uber is an app-based transportation network and taxi company. In its Airport rides in a particular city, many of its users face the problem of cancellation by the driver or non-availability of cars.

These very issues impact the business of Uber and it loses out on its revenue.

Approach:

The primary approach is to use EDA operations like univariate and segmented univariate analysis to identify problems and tackle it.

Using the data set available, we make use of R, a statistical computing program to perform various EDA (Exploratory Data Analysis) operations and hence find out the results. We make use of ggplot2 package of R to plot graphs.

Inference:

To come up with solutions to address this Supply-Demand issue and recommend realistic, actionable solutions.

Problem Solving Methodology

Initial Analysis: Understand the dataset given. Look through its structure, identify the datatypes of various columns and get a basic idea of the dataset to proceed further.

Data Cleaning: Look out for visible data quality issues and rectify them. Check for blanks, duplicate data and convert certain columns to required datatypes.

Exploratory Data Analysis: Making use of Power BI query editor , carry out various EDA operations like Univariate and Segmented Univariate analysis and come up with intuitive insights of the Supply-Demand problem.

Visualization: Make use of various graphs in BI to plot various graphs with proper aesthetics and geometry, clearly displaying important insights.

Recommendations to Resolve the Supply-Demand gap.

1.Uber should provide higher monetary incentives for driver taking a Peak Morning trip from City to Airport.

2.Setting targets for drivers to take up the City to Airport or Airport to City trips and then suitably rewarding them through lucky draw schemes, gift vouchers.

3.Incentivize Airport to City trips in the night so that more drivers from the City reach the Airport thus increasing the availability of the cars.

4.Ask its drivers to not retire from services early in the evening.

5.Conduct orientation classes for drivers and let them know about the insights obtained analysis of this problem so that the drivers know where to be at what time of the day.