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MIS781 Business Intelligence And Database
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MIS781 Business Intelligence And Database
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Course Code: MIS781
University: Deakin University
MyAssignmentHelp.com is not sponsored or endorsed by this college or university
Country: Australia
Question:
Tasks:
Develop the relevant BI dashboards and predictive models using IBM Watson Analytics tool. Please present the BI dashboards first, then followed by the explanation of each individual chart of the dashboard.
Justify why these BI solutions could provide insights and why those attributes are laid out in the fashion you proposed (feel free to include all other relevant justifications). Note: To ensure that you discuss task (2) properly, you must include visual samples of the reports you produce (i.e. the screenshots of the BI report/dashboard must be presented and explained in the written report; use ‘Snipping tool’), and also include any assumptions that you may have made.
The BI report should include: 1) objectives and benefits of your BI solution, 2) BI dashboards screenshots and commentary, 3) predictive models, 4) overall findings and recommendations, etc. Feel free to make reasonable assumptions or refine the data as needed. You may create your own artificial datasets. Real-world dataset is not compulsory. Note: Do refer to the assignment marking rubrics.
NOTE:
You MUST produce the actual visuals in IBM Watson Analytics.
If you think the best presentation above is to use, say, only a pie chart, then discuss using a pie chart and indicate what the pie chart would show, why you picked the pie chart, and so on.
It may be useful to try with various dashboards (i.e. combinations of presentations) before rushing to conclusion.
Answer:
Introduction
Use of BI (Business analytics) helps the business organization in order to have a data-driven approach to know and compete in the competitive business environment through the use of the data modelling and statistics to develop improved business insights. This combination of business and technology makes it the best strategic tool for organization to handle, process and get insights from big data collected from different sources. Furthermore, the data analysis and business intelligence tools enables the organizations to create predictive modelling for their business. This is done through the analysis of the available data about a past performance of the flights and its business in order to predict the way it may perform in the future. Depending on the predictions the organizations takes business decisions accordingly for better performance.
Users explore data via visualizations, natural-language-generated narration, search and NLQ technologies.
Business intelligence
Business Intelligence or BI is generally referred to the applications and technologies utilized for the collection, analysis, presentation and integration of the data and information generated in the business process. In the contemporary times, business process does not regard data and content as separate aspects. Instead it is nowadays utilized as an integrated approach for enterprises. For aviation industry as well, it is considered that all the predictive, current and historical data for the business operations will be handled easily with the help of Business Intelligence applications and technologies.
It has been found that the traditional technologies that were in use in the aviation industry had plagued the system with faulty handling of business data generated every day. Business Intelligence in the aviation industry does not only take heed of the passenger details and flight history or data for a particular aviation organization, but also generates information about the condition of the flights and the feedback data of the passengers. Without the implementation of the Business Intelligence application and technologies, there have been incidences reported where the flights have been found to have dirty and unhygienic environment and uncomfortable seats. The application of Business Intelligence does not disregard these minute factors of the aviation industry as well. Missing out on these minute data might cause unrest within the passengers, which in turn would result in loss of the business organization in the long run.
Business Intelligence is generally utilized in the aviation industry for the better analysis of data generated, which would further enhance the ways by which decision is made in the organization. Decision making is a major aspect for any business organization that is a decisive factor of the future of the organization as well as the industry in which the organization deals. Faulty handling of data often makes it difficult to reach to a conclusion to make an effective decision in favour of the organization. It has been noted that over the past few decades, the innovations and business decisions that has been taken in favour of the aviation organizations in Australia have all been mediocre in their actions, which has resulted in lousy customer services. Perhaps it can be noticed that more than any other industry, the aviation industry requires the utility of Business Intelligence the most.
For the business analysis project there are multiple tools that can be used for analysis of the datasets. Following are few of the tools that can be used;
Analytics Dashboards: The capacity to make profoundly intelligent dashboards and substance with visual investigation and implanted progressed and geospatial examination to be devoured by others.
Intuitive Visual Exploration. Empowers the investigation of information through a variety of representation choices that go past those of fundamental pie, bar and line outlines to incorporate warmth and tree maps, geographic maps, dissipate plots and other unique reason visuals. These apparatuses empower clients to examine and control the information by collaborating straightforwardly with a visual portrayal of it to show as rates, canisters and gatherings.
Data Discovery: Automatically finds, envisions and describes essential discoveries, for example, relationships, exemptions, groups, connections and expectations in information that are applicable to clients without expecting them to manufacture models or compose calculations. Objectives and benefits of the BI solution
Business Intelligence always opts for providing the best possible analysis to make an industry take effective business decisions. It is found that, with the implementation of Business Intelligence it has been possible that in today’s time aviation industry is at that point of innovation that it can effectively utilize the big data analysis techniques to make effective decisions regarding the business. Following are the benefits by which the aviation industry in Australia has been endowed with the implementation of effective Business Intelligence or BI solutions:
Flight schedule managements and reduction of cancellations:Reports have predicted the facts that the pilots in a flight are soon to be replaced with that of Artificial Intelligence enabled robots. However, in reality, the situation is a tad different as there has been an overflow of pilot shortages. Pilot shortages have resulted in cancellation of flights which has made aviation industry lose millions of dollars. This problem has found a solution with the implementation of the Business Intelligent solutions that provide an application specialized in generating sophisticated flight schedule management systems. This technology has made it possible for the organizations to utilize Business Intelligence in developing pilot utilization to keep the flights flying and reducing flight cancellations altogether. The technology has the ability to locate the delays that occur within the daily operations and utilizes intuitive visualizations to alert the schedulers of the crew and solve all the issues to before the flight gets cancelled.
· Prescriptive Maintenance for Accurate Decision Making: Maintenance problems are reduced at a noticeable rate when Business Intelligence is utilized to make positive changes in the aviation industry. Since the aviation industry has adopted the technology of Internet of Things or IoT, the massive amount of data generated each day by the aircraft sensors are easily maintained by advanced methods. In addition to that, the aviation industry utilizes predictive methodology for the generated data. This Business Intelligence method for the predictive data maintenance provides the crew with the information about a particular object, system or item on how long it can be utilized to its full potential. Based on that, the crew can make sure of the utility of the item, object or system before replacing it with a new one.
Chatbots for improved customer services: One of the major advantages that Business Intelligence has provided the aviation industry with is freeing it from its ill-reputation of providing bad customer services. There are many noticeable issues in the airlines and aviation industry about customer services being rude to the clients and having severe issues with the ticketing and accommodation services. Thus, the BI technology has presented the aviation industry with chatbots. Chatbots are the business intelligence solutions that realises the basic requirements of a customer and readily fetch the information that have been asked for. In addition to that, these chatbots are never rude to the customers and provides them with ready solutions at any given point of time since they are active 24/7.
· Implementing Robotics for Safety and Quality: It has been found that in the aviation industry, the huge amount of generated data has made it very difficult to accurately analyze and make a decision based on them. Thus, the safety of the aviation industry is also affected by this. It has been reported that before the implementation of Business Intelligence in the aviation industry, the wrong choice of decisions has resulted in 6.2 percent of the industry employees to sustain several injuries alone in the year 2015. Therefore, the technologies of Business Intelligence have made intelligent and automated manufacturing processes for the aircraft that provides a much smaller window for any possibility of human error and an injury further making use of the artificial intelligence enabled robots to take decisions for aircraft manufacturing.
Assumptions made for this project
For this business analytics project some assumptions are made which are can impact that airline industry and specifically for the organizations that operate in the region. Following are the assumptions for this case;
The organizations maintain their business strategy same for the period while the dataset is collected.
All the internal and external factors affect the concerned organizations in the same way.
All the organizations in the data set operated the same number of flights in the routes which were not changed at the time of collecting data.
There is no inconsistency in the selected data set for analysis.
BI Dashboards and commentary
Cancelation of the flights organization wise is given by the following dashboard,
Following is the comparison of the Quantas and Virgin Australia for the cancellation of flights,
From the above dash board, it is evident that, Virgin Australia has the highest calculation rates of the flights compared to the Quantas airline organization. The highest number of cancellation happened in the month of July,2016 which sums up to 1124.
The number of Distinct routes in which the Quantas and Virgin Australia is operating is provided by the following dashboard;
It is evident from the above dashboard that Virgin Australia is operating in 121 routes where as in case of Quantas it operates in the 73 routes.
Following is list dashboard that depicts the trend in the delays by Quantas as well as Virgin Australia.
From the above dashboard it can be said that the lowest number of cancelations for Quantas was in the February, 2016
The drivers behind the cancellation of the flights are depicted in the below dashboard,
The strongest factors that influences the rate of cancellation for the different flights that are present in the dataset are given by,
Arriving port and Airline
Airline and departing port
Different combination of this factors with some other elements are most impactful on the cancellation of the fights.
In the next section, the airports that are responsible for most number of delayed departures of the flights by the Quantas airline.
According to the above dashboard it can be stated that there are mainly six airports that are mainly responsible for delayed departures. The Chocolate segment in the pie chart represents all other airports which we are excluding in our analysis project. Now the light green coloured sections represents the Sydney airport, dark green section represents the Melbourne airport and lastly the light blue colour represent the delayed departure from the Brisbane airport.
Recommendations
From the above analysis it can be stated that even though the Virgin airlines is operating in more routes compared to the Quantas but the quality of service is always below Quantas from the perspectives of onetime arrivals, departures and cancellation. Therefore, following are the recommendations that can help Virgin Australia in order to acquire better market share in the industry.
The Virgin airlines needs to improve its departure timings of the flights as it is found that there are more number of delayed flights of Virgin airline compared to Quantas.
More over the Virgin airlines should try to improve its timings at the airports that mostly contribute to the delayed departure of the flights. This airport is listed as below,
Challenges in the effective use of business intelligence for the organizations
1) In the utilization of the BI and analytics the most important issue is identification of the relevant and meaningful metrics and measures vital for the industry and business through the proper monitoring and analysing in order to improve decisions as well as actions.
Improved decisions and consequently the concerned actions contribute to better business performance through the improvement of the right metrics of the business. Use of the BI in different departments would have desired impact as long as all of them work as single systems with stream lines inputs and outputs.
2) In order to use the BI and result of analytics effectively it is important to ensure the availability of clean data from different sources. This data may include data concerning the existing and loyal customers from different airports or sectors which is not mentioned presently in the selected data set in order to provide better service to the customers. From the previous different projects, it is found that the in case of BI project and data warehousing the above mentioned were described as a big challenge for usage of BI in order to improve business.
3) The business analytics and implementation of different processes required collaborative effort from different departments with significant amount of input from the top level management and executives in the organization.
4) It is seen that for the vast majority of the organizations uses Business intelligence application and its outcomes to help the top level administration of the associations as the aftereffects of the examination encourage their requirements better. Though the need is to prepare the line administrators additionally with operational business insight to help them in their work.
5) The professionals from different departments are required to have quantitative aptitudes and furthermore be technically knowledgeable to use the insights availed from the BI tools.
Scope for further research
Research methodologies that have been utilized in this matter have led to a certain stage of results which are satisfying the entire research for now. However, there is always a scope for further research given the vast possibilities of the utility of Business Intelligence adoption in the aviation industry. It has been noted in the aviation industry, the data generated are huge in number. The amount of data utilized for this research has been limited to a certain level that has resulted in limited scope of research for the aviation industry.
Therefore, ideally there could have been a much broader prospect of applying the data to use if there had been much more data available to identify the problems that aviation industry has been facing at the recent times. This would have further resulted in making decisions based on the analysis of the provided data to make sure about the hazards that the aviation industry faces every now and then without the use of Business Intelligence technologies and the after effects of utilizing the same. The general aviation operations go through several problems throughout the day and thus the assumptions made at the end of every working day is subjected to changes. In addition to that, there has been a restriction in the research process with provisions regarding the customer related data. Therefore, as per the scope in the research, there would have been much more possibility for systematic analysis based on the customer related data. This would have made a scope of further advancements in the research by providing a detailed informative analysis to the customers so that they would have the information about availing the best possible aviation services based on the results of the research. Thus, collectively, it can be said that if there was an availability of more generated data, especially the customer-related ones, there would have been scope of a much detailed research made over the aviation industry and its implementation of Business Intelligence technologies.
With the results of data analytics, it can be said that the selected airlines can be able to respond to the trends and issues more rapidly in order to match and improve with the ever changing aviation industry conditions. The reason behind this can be states as with the frequent use of the data analytics and it will have faster access to the data related to their operations. With the improved data analysis of the it will contribute to the Virgin Airlines in its improved growth while resolving the issues relate to the operation.
Conclusion
With the above data analysis project using the data analytics tools it enables the business organization to take better as well as faster decision making from the available of insight. In this way the insight will balance the organizations capability to respond rapidly with clear business strategy.
In this way it will let the organization know whether the selected business strategies/ actions taken for improving the business are appropriate or not. Moreover, the organization will be able to find if some internal factors are holding the business organization back. If there are any issues are found, then the possible solutions also can be sorted out through the improvement of processes.
In addition to that, the business intelligence is also helpful in the conducting competitor analysis in the market comparing the performance with others. With the clearer idea about the idea about the competitors through the data analytics insights can help in determining the strategies to which the competitors are up to.
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