HeyIn this assignment we have to choose 4 different topic and topic will be Effects of Data Minning on banking,education industry and so on which are given in the PDF which I am submitting. and plese...

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Table of Contents
Potential impact of business analytics and Data mining techniques on transportation industry    4
1.    Introduction    4
2.    Added values to transportation industry by business analytics and Data mining techniques    4
3.    Faced challenges to transportation industry because of business analytics and Data mining techniques    5
4.    Conclusion    6
5.    References:    7
Potential impact of business analytics and Data mining techniques on banking industry    8
1.    Introduction    8
2.    Added values to banking industry by business analytics and data mining techniques    9
3.    Faced challenges to banking industry because of business analytics and Data mining techniques    10
4.    Conclusion    11
5.    References:    11
Potential impact of business analytics and Data mining techniques on healthcare industry    12
1.    Introduction    12
2.    Added values to healthcare industry by business analytics and Data mining techniques    13
3.    Faced challenges to healthcare industry because of business analytics and Data mining techniques    13
4.    Conclusion    14
5.    References:    15
Potential impact of business analytics and Data mining techniques on education industry    15
1.    Introduction    15
2.    Added values to education industry by business analytics and Data mining techniques    16
3.    Faced challenges to education industry because of business analytics and Data mining techniques    17
4.    Conclusion    18
5.    References:    18
Potential impact of business analytics and Data mining techniques on transportation industry
1. Introduction
The transportation industry is very large industry and making use of techniques from data mining to make sense to business analytics. The results of data mining can help in making control on the city traffic, planning the traffic routes and effective management of city traffic by making certain predictions related to traffic conditions. In today’s world, each user wants to save time and money, so, implementation of data mining techniques on transportation industry can help users ton archive so. The logistic movements are most essential for traders and effective business analytics with techniques of data mining can solve this logistic management issues. The optimization of traffic movements leads to competitive advantages to transportation industry because of data mining. The technical involvement of data mining in transportation industry is increasing the business aspects for organizations and better forecasting of possible traffic conditions helps them to effectively manage their routes [Bandis et al, 2018]. The turnover risks to transportation industry can easily be reduced by the help of data mining. The capacity constraints and delivery routes of certain products can be decided by transportation industry with data mining and business analytics. The best transport method, delivery route, traffic control, traffic frequency and maintaining the delivery time can easily be analyzed with techniques of data mining on bases of collected data from past experience.
2. Added values to transportation industry by business analytics and Data mining techniques
The technological involvement always leads to some added values to all business domains like transportation industry. The possibility of e-logistics based on the traffic and natural conditions is archived by the data mining to transportation industry. The results based on algorithms and provided decision tools helps in effective analysis to possible options by making careful predictions. The transportation industry is making so many gains and different values are added to this transportation industry because of data mining techniques [Noulas et al, 2015]. The points holding important added values to transportation industry because of data mining techniques and business analytics are supplied below:
· The transportation industry works on the traffic conditions, so, effective analysis with data mining techniques will helps to manage traffic conditions and adds values to this industry.
· The tourism industry can make certain arrangements and can plan their routes based on the provided results. This will enhance the revenue and justifies the implementation.
· The implementation of transport system, route management, traffic management and making predictions for saving time and money can be provided by data mining techniques results [Ying, 2016].
· The decision making capabilities of stakeholders will also improves and this is main added value to this transportation industry because of data mining techniques.
3. Faced challenges to transportation industry because of business analytics and Data mining techniques
The implementation of each new technology for any industry like transportation industry mostly leads to certain challenges. The industries have to face and overcome to the identified challenges by providing a suitable option. The techniques of data mining and business analytics will add challenges to transportation industry as well. The points holding important identified challenges to transportation industry because of data mining techniques and business analytics are supplied below [Fredriksson et al, 2017]:
· The transportation industry mostly works on the SCM concepts. The effective coordination is required implement in SCM faces challenges of revenue and cost management.
· The transportation industry needs real time data for deciding the routes. The analysis of real time data is highly challenging for transportation industry.
· Transportation industry includes trucking industry, rail lines, air cargo and so many other systems. So, implementation of same system to all the different domains will lead to challenges for transportation industry.
· The implementation of data mining to transport industry requires well qualified staff to make predictions and improve the business conditions but in transport industry it adds additional costs.
· The predictive analysis based on data mining techniques for analysis of real time data creates problems for business domains like transportation industry.
4. Conclusion
The involvement of any new technology to any industry like transportation industry defines new growth opportunities and improves the performance with effective results. The risk management becomes easy for transport industry because of data mining techniques. The regulatory requirements can easily be identified based on the business analytics results from techniques of data mining. The association of big data can assure the collection of relevant business information to transportation industry. The business management of transport industry can easily be improved based on the emerging technologies of data mining. The technical involvement of data mining in transportation industry is increasing the business aspects for organizations and better forecasting of possible traffic conditions helps them to effectively manage their routes. The turnover risks to transportation industry can easily be reduced by the help of data mining. So, implementation of data mining techniques to transportation industry will provide new values and makes easy monitoring of traffic conditions to save time and money. The regulatory requirements of transportation industry can easily be managed with techniques of data mining.
5. References:
Bandis, E., Petridis, M., & Kapetanakis, S. (2018). Predictive process mining using a hybrid CBR approach for the rail transport industry. ICCBR 2018, 175.
Fredriksson, C., Mubarak, F., Tuohimaa, M., & Zhan, M. (2017). Big data in the public sector: A systematic literature review. Scandinavian Journal of Public Administration, 21(3), 39-62.
Noulas, A., Salnikov, V., Lambiotte, R., & Mascolo, C. (2015). Mining open datasets for transparency in taxi transport in metropolitan environments. EPJ Data Science, 4(1), 23.
Ying, C. (2016, June). Intelligent Transport Decision Analysis System Based on Big Data Mining. In 7th International Conference on Education, Management, Information and Computer Science (ICEMC 2017). Atlantis Press.
Potential impact of business analytics and Data mining techniques on banking...