Aim and Objectives of the Research Study

In simple words, it is an effective tool through which computers and humans work together, making the work easy and simple (Korbicz and et.al., 2012). Even though AI techniques like machine learning are not new to business world but the changes that has taken place in this area is tremendous. Over many years, accountants have embraced waves of automation in order to improve the effectiveness and efficiency of their work. However, till this time technology has not been able to replace the requirement of decision making and knowledge. Use of human experience limits the machines (Brodie and Mylopoulos, 2012).

Accountants aim at providing advice and effective decisions so that they can support firm and economic to work better. All activities related with accounting make companies to take decisions for allocation of resources and making the business reach their goals. Organizations working in financial sector or provide financial services adequately utilize artificial intelligence in order to provide precise advice of investments to their customers, giving them guidelines about their financial positions and for gaining the competitive advantage. The present study is focused on identifying the effectiveness of artificial intelligence and integrated data mining. These are helpful enough for the companies to improve their financial and operating performance and also influence in decision making by management.

More specifically, Apart from this, this study also discusses the research methodology that research will be going to use in order to accomplish the aim and objectives of the research study. This study also carries out pilot data collection where research will obtain data by using various sources. Thus, in this manner, will be able to accomplish the aim and objectives of the research study.

Significance of research

Main focus of the study is to provide viewers regarding artificial intelligence and integrated data mining. Artificial intelligence and integrated data mining. Further, it helps the corporations working in every sector by reducing their time consuming efforts and simplifying the process of data analysis. In this manner, this research study will be significant for people working in financial consultancy services or financial sector as they will be enhance their information and education about the concepts of artificial intelligence and integrated data mining. Apart from this, it also includes importance to manufacturing sectors at Canada and accountants working with the help of Artificial intelligence and integrated data mining.

LITERATURE REVIEW

Artificial intelligence and integrated data mining

As per Brodie and Mylopoulos, (2012) AI is so powerful and enables to create quick information. Further, it also help in extracting accurate data that accountants can use in making decisions. In decisions making there are two ways that humans consider, these are reasoning and intuition. Reasoning is a part in which individuals focus on answering the questions. On the other hand, thought process in unconscious and instinctive, thee take place very quickly. With AI, accountants are able to determine the condition or situations that are faced by the firm and as per that data provided decisions are made.

Further, it also build into rules engines which make recommendations or decisions. According to André et.al., (2018) artificial intelligence is an area of computer science that emphasizes on the development of intelligent machines that work and react like humans. Artificial intelligence is considered to be a tool of business which helps in enhancing the performance of business exponentially especially in the areas that requires great deal of precision, accuracy and analytical decision making. Ebert et.al., (2018) elucidated that besides supply chain management, research and development (R&D), sales and marketing, human resource management, the impact of artificial intelligence has been felt more on accounting which is a field that requires highly skilled and technically qualified professionals.

According to Carlos, Kahn and Halabi, (2018) big data refers to the systematic collection of ample amount of novel data which has been stored by the organizations for the purpose of analysis and dissemination. The three prominent characteristics are associated with term Big. These are Volume, Velocity and Variety. Volume refers to the size of collected and store data through records, transactions, files, tables, spreadsheets, etc. The rate at which data is been exchanged marking it as Big Data analysis is known to as Velocity. It can be exchanged in real time or near real time. Variety refers to the numerous forms in which the data is received or delivered. Stach and Maruyama, (2018) argued that indeed artificial intelligence and big data have significantly transformed the accounting procedures and process of the organization but it also increases the complexities and search for highly skilled and technical personnel.

In year 1955 John McCarthy who was researching about AI included that performance of machine or technology which will be requiring intelligence if it is performed by humans. So it will be meaning that investigating intelligent related to problem solving behaviour and thus creating intelligent based on computer system. According to Russell and Norvig, (2016) there are two types of AI namely weak and strong artificial intelligence. In weak AI the computer which is used as merely instrument of investigating while in strong AI it will be used as intellectual self-learning process. Under this system computers will be understanding all human behaviour or working as per their own and experience as well. Best assignment help in the United kingdom from experts.

Use of mining data gathered on business process in eliminating inefficiencies and minimizing expenditure

According to Helbing and et.al., (2017) data mining is a technique for searching large scale database for patterns, used mainly to find previously unknown correlations between variables that may be commercially useful. The automatic practices of identification of patterns and trends within large stored data which goes beyond accurate analysis is refer to as data mining. Russell and Norvig, (2016) elucidated big data analysis or the mining of extremely large data sets used to identify trends and patterns which is increasingly becoming standard practice of business. Companies always seek for measures which could help them in reducing the costs, increasing revenue and gain competitive advantages. Collating and harnessing data is now considered to be most crucial method to achieve these objectives. In this context Ebert and et.al., (2018) proposed that real time data provides companies visibility into the current performance, costs and trends whereas in the past that data would have been historical and deemed less useful due to it being outdated. Real time data allows companies in reducing issues and challenges and also provides them insight for future planning.

Russell and Norvig, (2016) elucidated that analyses data provide assistance in improving customer satisfaction. It helps the logistics managers to select best and efficient methods of shipping by utilizing best carriers to limit damages and cease delays thus enabling better services to the customers. This helps manufacturing industries in creating better relationship with customers. Helbing and et.al., (2017) elaborated that producers are now finding variety of models for business, which are enhancing and improving quality of products and optimize manufacturing operations. Through automating optimization of inventory by utilizing machine learning, significant improvement has been observed thus, simultaneously increasing the inventory turns of manufacturing sector. This ultimately helps in reducing the inefficiencies and minimizing the expenditure of the companies.

AI is transforming the way in which humans live and they are working which is helping in repetitive task that is personalising products and services for consumer. Like for example AI could be developing intelligent robots that are holding information and sending them to defusing bombs and reducing risk to human life. As per Dilsizian and Siegel, (2014) the AI technologies are growing up to as important feature of daily human life and also part of diverse functions of business. Economy and society are also facing disruptive impacts or effects of AI within this short span of time after the introduction of this AI. The most essential factor of technology within this workplace is the effect of business economics which is depicted to as replacement of humans to robotics.

Utilization of Artificial Intelligence and mining data to enhance financial performance and business operations

According to John, (2015) Artificial Intelligence is machine or ability of machine to replicate cognitive function of human beings. It has ability to comprehend and solve complex problems. In computer science, these machines are aptly called as an “intelligent agents” or bots. Stone, Neely and Lengnick-Hall, (2018) elaborated that in present world the technological advancement reached its apex and going beyond it continuously. Quality of products and services are enhanced, financial position is stronger than that of others in industry which is due to introduction of robots and machines within manufacturing sectors. Reduction of faults within supply chain management till 50% and that of sales by 65% so that product is been available is positive side of Artificial Intelligence (AI) Stone, Neely and Lengnick-Hall, (2018) argued that artificial intelligence and mining data not only aid in strengthening the financial performance of the organization, it also helps in detecting the fraud statement proposed by the management of organization. Stach and Maruyama, (2018) said that top management is usually found responsible for fraudulent reporting of financial statements to fulfil the objective of artificial improving the financial performance and results of the company.

All the trading firms will be including AI and machines as using their data and information which is improving ability of firm to sell all their products to their clients. Like analysing trading behaviour which is anticipating a next order of their client and then generating larger quantities of data.

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Aim of Research

Revenues raised from big data analytics through immense increase in business valuation

According to Carlos, Kahn and Halabi, (2018) to sustain in the competitive environment it is essential and necessary for the business organization to utilize the latest technologies which helps in reducing their efforts and provide assistance in creating revenue. In order to inculcate the data, managers utilized different ways and tactics that help them in providing comprehensive understanding of the data. The collated data utilized by the data scientists of manufacturing sector in precise and adequate manner so that meaningful information can be obtain and strategies can be implant within the organization in order to enhance the profitability and revenue of the company. Korbicz and et.al., (2012) elucidated that it becomes difficult and challenging for the management to compute the humongous data by using traditional method. In order to simplify the calculation process, the management install and implemented latest and advance technologies which helps in providing precise calculations in no time. The most challenging and complex task which are faced by the management of business organizations are making decisions.

Internet of things is network which is regulating physical device and home appliance which is included into electronic and form of software which is all connected to an exchange of data. It was included by Helbing and et.al., (2017) there are number of devices which are increasing and reached to 31% per year to 8.4 million within 2017 and thus it would be included till 8.4 billion till 2020.

Rationale of research

With advancement in technologies the business operations of organisations has been enhanced tremendously. Thus, through this research will be able to enhance his or her level of knowledge effectively about the use of artificial intelligence and integrated data mining. Through this also be able to get familiar with manufacturing industry sector in Canada as data will be obtained from the people working in these services. This study enhances knowledge level of regarding efficiently embroidering the research paper.

Research aim and objectives

Aim: The aim of the research study is to analyses the effectiveness of artificial intelligence and integrated data mining: A study on manufacturing industry sector at Canada.

Objectives:

• To identify the use of Artificial Intelligence and mining integrated data which enables organizations in better comprehension of their own business and industries through utilisation of analytics based on high quality data.
• To investigate the utilisation of Artificial Intelligence and mining data to enhance financial performance and operations of organizations and engage in compliance.
• To identify the ways through which organizations can identify their opportunities from big data analytics through immense increase in their business valuation.
• To examine the ways through which mining data on the process of business could be used to recognise and eliminates inefficiencies and risks systematically.

Hypothesis:

• Artificial intelligence and integrated data mining is not effective for manufacturing industry sector at Canada.
• Artificial intelligence and integrated data mining is highly effective for manufacturing industry sector at Canada.

Research Questions

1. How Artificial Intelligence and mining integrated data enables manufacturing sector in better comprehension of their own business and industries through utilisation of high quality analytics?
2. How organizations would identify their opportunities from big data analytics through immense increase in their business valuation.
3. What is the use of Artificial Intelligence and mining data to enhance financial performance and operations of manufacturing sector by engaging in compliance?
4. What are the ways through which mining data on the process of business could be used to recognise and eliminates inefficiencies and risks systematically?

RESEARCH METHODOLOGY

Research methodology is considered to be the framework of the research study. In order to attain the aim and objectives of the research study, it is essential as well as crucial for the to describe the methods of inquiry in effective and efficient manner (Taylor, Bogdan and DeVault, 2015). The research philosophy, research approach, research design, and research strategy will be described. The explanation of the methods of collection of data, sampling and analysis and eventually the ethical issues that occurred during the study will be discuss.

Research philosophy

In this context, positivism research philosophy has been used in the research study. Positivism adheres to the perception that only factual knowledge can be acquired from observation (Taylor, Bogdan and DeVault, 2015). In the present study, inductive research approach has been used. Inductive research approaches centred on research questions and assists in analysing aim and objectives of the study. The design of present research study is descriptive as in the study an attempt to provide elaboration about the analytical research has been made so qualitative is used.

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