The Impact of Data Mining in the Automotive Industry: An Analysis

This report examines the profound impact of data mining on the automotive industry. It begins by highlighting the increasing importance of data mining and its benefits, particularly in predictive analysis and business process improvement. The report details how data mining enhances various aspects of the automotive industry, including design, marketing, and fuel management. It explores the integration of data mining across different departments, such as market analysis, legal compliance, and architectural design, facilitated by AI. The report then analyzes the processes before and after data mining implementation, focusing on events, activities, decision points, actors, and outcomes. It includes process model diagrams illustrating the differences in data flow with and without data mining. A transcription of a video discussing the benefits and disruptions of data mining in the automotive sector is also provided, emphasizing the technology's role in enhancing decision-making and improving client satisfaction. The report references several sources to support its findings, offering a comprehensive overview of data mining's transformative effects on the automotive industry.

Running Head: IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Name of the Student
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Author Note

1IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Table of Contents
Part 1..........................................................................................................................................2
Part 2..........................................................................................................................................2
Part 3..........................................................................................................................................3
Part 4..........................................................................................................................................4
Process model diagram..............................................................................................................6
Transcription..............................................................................................................................8
References..................................................................................................................................9

2IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Part 1
Data mining technology have been gaining importance in a drastic rate. Analytics is
the process that is benefitted. This technology have been a major change that has been
influencing the process of data analytics. Predictive analysis with the help of the usage of the
data mining technology have been bettering the business making process of the automotive
industry. The data that are collected ensures the fact that the accuracy of the collected data
will be very high (Al-Mubayyedet al, 2019). Hence if the doling out of the business
organization was performed the main instance that is considered includes better marketing
processing of the automotive industry. Data mining also helps the automotive industry in the
process that will ensure that better execution of the designing process can be made. This is
one of the chief aspect that proper implementation of the architecture process can be
performed in a better and accurate manner. This aspect delivers improved understanding of
the architecture that will be benefitting the functional process of the automotive industry.
Part 2
3 processes by which data mining will incorporate eruption are as follows: -
 Understanding of the design that will be helping in bettering the design system will be
beneficial in the processing of the efficiency increasing process. This is one of the
major instance that benefits that are gained as per the execution of the project of
automotive includes the issue that understanding of the issues that have been
occurring in the process of the designing (Santos et al, 2017).
 Marketing of the products are another major aspect that increases the processing of
the data mining functioning. Again with the help of the data mining understanding of
the business management system requirement of the clients gets enhanced and hence
the understanding of the need of the customers gets easier. With proper understanding

3IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
of the requirement proper advertisements can be made as per the commencing of the
needs of the clients.
 Fuel management via data mining gets easier. With the help of fuel mining the main
advantage that will be receiving includes the fact that clients will be getting positively
affected (Yan et al, 2017). This imbibes that the data regarding the fuel present in the
car is measured and provided to the driver or owner of the car. Hence management of
fuel gets easier.
Part 3
Market: Data mining has been providing high facilities to the automotive industry
internal stakeholders. With the help of data mining it gets easier for understanding the needs
of the people who will be using the automotive (Cheng et al, 2016). This guarantees that the
data that are poised can be used for creation of the architecture in a manner that will satisfy
the requirement of the stakeholders and hence the architecture process will get enhance and
hence capturing of market will get easier.
Law: Data mining helps in getting accustomed with the legal issues that are faced by
the previous brands of the automotive. This helps in bettering the processing of the business
management section. This will ensure that proper management of the legal abidance will be
present and hence legal issues can be mitigated. This will help in better commencing the
business management.
Architecture: Artificial Intelligence are the major introduction that helps in bettering
the functioning system of the automotive industry. This enhances the fact that
implementation of AI the decision making process gets easy (Purr et al, 2016).
Norm: Ethical dilemma is present in the system. Due to the implementation of data
mining the main feature that is occupied into contemplation includes the fact that data that are

4IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
collected are stored and hence kept as the reference set and used as exemplary. This enhances
the fact that the privacy issues can be mitigated. Hence inclusion of this issue has been the
major reason of the data segmentation and not much inclusion of the technology
Part 4
Before implementation
Events
Surveys are conducted for understanding the requirements of the project. This ensures
that collection of data for understanding of the project management process will get affected.
This will ensure that the data that will be collected will enhance the commencing process of
the business management (Witten et al, 2016). Hence architecture process is performed as per
the data that are generated via the survey that is conducted. With the help of the statistics
poised enhancement of the architecture process was performed. Sample population is used for
this process.
Activities
Preparing of the data modelling as per the interviews that is conducted requires a
vivid set of activities. These activities includes making questionnaires. Setting up of the
survey team. Taking into consideration of the random sample, conduct the survey (Kašćelan,
Kašćelan & Novović Burić 2016). After conduction of the survey the main aspect that is
considered is that better management of the architecture development. After the data is
collected, proper analysis of the data will be made. Hence the analysis of the data will be
effecting the architecture in a proper manner,
Decision points

5IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Decision points are not highly rated as the data that are collected are due to the
manual research processes.
Actors
Internal and external stakeholders of the automotive industries are the actors of the
project.
Outcomes
The outcome that is gained includes the fact that it is not much innovative and the
entire process is laborious.
After Implementation
Events: Architecture process has been getting benefitted and hence the
commencement of architecture gets performed in a manner that will benefit the designing
process. With the help of the data mining process, the main advantage that is received
comprises of better understanding of the required architecture with the data that are already
gathered. With AI implemented in the process of the data analysis the decision making
process gets easier and hence choosing of the architecture also gets easier. This ease in the
decision making regarding choosing of the architecture as per the analyzed data, accuracy of
the decision making also prevails. This high accuracy insists that proper management of the
architecture that is selected will yield higher efficiency (van der Vegte 2016).
Activities: the activity list enrolls the processing of the data analysis via data mining
process. With the help of the data analysis proper decision making regarding the selection of
the architecture can be made. Hence proper understanding of the client requirements can be
estimated and predicted. This prediction will be based on the history of the client’s
requirement. This process is considerably much cheaper than that of the traditional method.

6IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Decision points: Decision point acts vital in the process. The chief feature that the
vitality of the project remains in the section that commencing of the project gets better. This
is one of the key characteristic that proper thoughtful of the business management gets made
in a manner and hence decision making with the help of the collected data gets easier. With
higher accuracy in the collected data decision point gets more efficient.
Actors: Internal and external stakeholders of the automotive industries are the actors
of the project.
Outcome: Highly positive outcome is desired with high return of the investment in the
process.
Process model diagram
Without data mining
Figure 1: Process model diagram
(Created by author)

7IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Data mining implemented
Figure 2: Process model diagram
(Created by author)

8IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
Transcription
Hi, hope you are having a nice day.
This video discusses about the benefits and the disruption that is brought into the field
of the automotive industry. This ensures that the data mining in the field of automotive
industry will be providing higher benefits and increase the efficiency in the process of
management of the system. In the initial stages of the project the main aspect that is taken
into consideration is that the data that are used via the platform of data mining helps in
having higher accuracy in decision making of the strategy implementation process. With the
help of the data mining process proper understanding of the architecture that is to be
implemented for fulfilling of the demands of the clients can be well understood. This ensures
that the benefits that they want from the automotive industry will be received by them as the
architecture is designed as per their demands and needs. Another major benefit that will be
received by the automotive industry includes providing higher efficiency in the marketing
sector of the business management. With the help of the projection of the data management
section and collection of the data that are required for understanding the needs of the client’s
proper advertisements can be created. With proper creation of the advertisement reaching out
the people and the mass gets easier. Hence benefitting the processing of the business
management of the automotive industry. As per the industry norms, few ethical issues are
also present in case of the data mining technology, the major ethical issue that is created
includes the fact that the data that is being analyzed or is compared via this platform gets
stored in the data base and hence privacy issues might arise. Hence ethical dilemma arises.
Despite tis ethical dilemma their are several advantages due to which the acceptance of the
technology has been very high.

9IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY

10IMPACT OF DATA MINING IN AUTOMATIVE INDUSTRY
References
Al-Mubayyed, O. M., Abu-Nasser, B. S., & Abu-Naser, S. S. (2019). Predicting Overall Car
Performance Using Artificial Neural Network.
Cheng, G. J., Liu, L. T., Qiang, X. J., & Liu, Y. (2016, June). Industry 4.0 development and
application of intelligent manufacturing. In 2016 international conference on
information system and artificial intelligence (ISAI) (pp. 407-410). IEEE.
Kašćelan, V., Kašćelan, L., & Novović Burić, M. (2016). A nonparametric data mining
approach for risk prediction in car insurance: a case study from the Montenegrin
market. Economic research-Ekonomska istraživanja, 29(1), 545-558.
Purr, S., Meinhardt, J., Lipp, A., Werner, A., Ostermair, M., & Glück, B. (2015). Stamping
plant 4.0–basics for the application of data mining methods in manufacturing car body
parts. In Key Engineering Materials (Vol. 639, pp. 21-30). Trans Tech Publications.
Santos, M. Y., e Sá, J. O., Andrade, C., Lima, F. V., Costa, E., Costa, C., ... & Galvão, J.
(2017). A big data system supporting bosch braga industry 4.0 strategy. International
Journal of Information Management, 37(6), 750-760.
van der Vegte, W. F. (2016, August). Taking Advantage of Data Generated by Products:
Trends, Opportunities and Challenges. In ASME 2016 International Design
Engineering Technical Conferences and Computers and Information in Engineering
Conference (pp. V01BT02A025-V01BT02A025). American Society of Mechanical
Engineers.
Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine
learning tools and techniques. Morgan Kaufmann.

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Yan, J., Meng, Y., Lu, L., & Li, L. (2017). Industrial big data in an industry 4.0 environment:
Challenges, schemes, and applications for predictive maintenance. IEEE Access, 5,
23484-23491.