Project Description
Automotive production and sales analysis is critical to optimizing production processes, evaluating sales performance and increasing customer satisfaction. In this project, we will evaluate automotive production and sales performance, customer satisfaction and service processes by analyzing production data, sales data, customer data and service and maintenance data. Our goal is to help automotive manufacturers and dealers improve their production, sales and service operations and make strategic decisions.
Project Usage Areas
This project has several uses for automotive manufacturers, dealer managers and data analysts:
Production Performance Analysis: Optimizing production lines and improving production quality by analyzing production data.
Sales Performance: Evaluating sales performance and trends by analyzing sales data.
Customer Satisfaction: Evaluating customer satisfaction and behavior by analyzing customer data.
Service and Maintenance Processes: Optimizing service processes and reducing costs by analyzing service and maintenance data.
Strategic Decisions: Developing and improving production, sales and service strategies using data analysis.
Dataset Description
The data set to be used in this project includes the data required to evaluate automotive production and sales performance. The dataset consists of four main files in total:
Production Data (production_data)
ProductionID: Production ID
PlantID: Plant ID
CarModel: Vehicle model
ProductionDate: Production date
UnitsProduced: Number of units produced
Defects: Number of errors
Sales Data (sales_data)
SalesID: Sales ID
DealershipID: Dealer ID
CarModel: Vehicle model
SalesDate: Sales date
UnitsSold: Number of units sold
SalesAmount: Sales amount
Customer Data (customer_data)
CustomerID: Customer ID
CustomerName: Customer name
Age: Age
Gender: Gender
city: city
CarModel: Vehicle model
PurchaseDate: Purchase date
SatisfactionScore: Satisfaction score
Service and Maintenance Data (service_data)
ServiceID: Service ID
CustomerID: Customer ID
ServiceDate: Service date
CarModel: Vehicle model
ServiceType: Service type
ServiceCost: Service cost
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate production and sales performance and customer satisfaction and make strategic decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
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