COIS13013 Business Intelligence

1. 

1. Discuss the importance of knowledge management in an organisation. Describe the technologies that can be used to support knowledge management.

Solution. The Knowledge management has greater significance. It is linked to the boosting of the efficiency within the organisation. There is a greater amount of decision making ability which tends to rise with the deployment of the Knowledge Management within the organisation (Almunawar et al., 2022; North & Kumta, 2018). The smarter work can be expected to be completed. The experience of the employees just forms an important part of the Knowledge Management System. There is a prevalent system which is part of the unique and also does offers greater benefits to the companies. The main goal which is well associated to it is to build up smoothness for the organization with the building up of greater levels of efficiency and to consider the alignment of the resources in a crucial manner (Almunawar et al., 2022; North & Kumta, 2018). The saving of the knowledge within the company and awarding the various practices tends to be useful (Li et al., 2019; Santoro et al., 2018; Demir et al., 2021). There is the deployment of the training and the learning that the organization has for its customers and various other stakeholders. The enhancement in the customer service and the satisfaction is also primarily important. The promotion of the innovation and the focus on the human development which comprises of the four crucial steps. The organize aids to consider the planning of the various processes and the subprocesses. There is an organized system which is part of the unique and also does offers greater benefits to the companies (Li et al., 2019; Santoro et al., 2018; Demir et al., 2021). The main goal which is well associated to it is to build up smoothness for the organization with the building up of greater levels of efficiency and to consider the alignment with the understanding, classification and the Sharing aspects. The Knowledge Management is being the set of systematic actions that are being utilized to facilitate the greater sharing of the knowledge. The appropriate policies, methodologies along with technologies that are implemented.

2. How is data analytics different from text analytics? Give three examples where data analytics is very useful for supporting business operations.

Solution. The Data Analysis considers the comprehensive process wherein the inspection, along with the cleansing, transforming and the modelling of the data is being carried out. The pace at which this takes place is also crucial (Li et al., 2019; Santoro et al., 2018; Demir et al., 2021). The goal aligned to the data analytics is the discovery of the information which is useful and the informing of the conclusions which can support the decision making process. The multiple approaches are being deployed to carry out the same (Vassakis et al., 2018; Wang & Xu, 2018). The Text Analytics on the other hand is a broader term and the technology is based on the identification of the deeper pattern and the trend based on the unstructured text. The text analytics is also deployed with the use of the understanding a negative spike in terms of the customer experience with the popularity of the product (Li et al., 2019; Santoro et al., 2018; Demir et al., 2021). The negative spike in the customer experience and the goal aligned to the data analytics is the discovery of the information which is useful and the informing with the popularity linked to the product. The examples where data analytics is very useful for supporting business operations is the various industries aligned to engineering wherein the source is required (Vassakis et al., 2018; Wang & Xu, 2018). Also the other example is the use in User Interface and User Experience for the websites that are developed for the enhancement of the business operations. The third is the utilization within the organization to extract the data of the satisfied customers for the business operations

3. What is the difference between a knowledge-based decision support system and a decision support system? Provide three examples on the application of knowledge-based decision support systems for supporting organisations.

There is a significant difference that lies between knowledge-based decision support system and the decision support system. The Knowledge Based Decision Support System comprises of the system which is being designed with the ensuring of the decision making with the effectiveness and the appropriate knowledge (Vassakis et al., 2018; Wang & Xu, 2018). The main goal is to effectively take the decisions. There is a greater amount of decision making ability which tends to rise with the deployment of the Knowledge Management within the organisation. The smarter work can be expected to be completed. The experience of the employees just forms an important part of the Kknowledge-based decision support system. There is relevant amount of knowledge which has the basis of the artificial intelligence and the application is reliant on the information along with the communication technologies. The application is being based on the recommendation techniques (Vassakis et al., 2018; Wang & Xu, 2018). There are various classifications and the non-knowledge. Reliant system utilizing the powers of machine learning. The decision support system on the other hand is the computerized program and the same is being used to the support for the judgements and the course of action taking place within the organization. The decision support system does sift and the analysis of huge data is also involved. The examples on the application of knowledge-based decision support systems for supporting organisations include the GPS route planning for the automobile servicing companies (Vassakis et al., 2018; Wang & Xu, 2018). Also the ERP Dashboards can be provisioned with its aid. The mapping in the education sector for the preparation of the learning maps for better decision making is also an example deployed in case of the educational institutes.

4. What are the three service models that provide the foundation to service-oriented DSS? Provide three examples of the three service models in organisations.

Sol. There are three service models that provide the foundation to service-oriented DSS (Masood et al., 2021; Moreira et al., 2018). These are the Data as a Service, Information as a Service and the Analytics as a Service. The Data as a Service has the examples as below –

• Provisioning of the useful data to the customers as part of the organization

• Making the finance data available to the customers

• Utilizing the concept of the Urban mapping which us the geography data service and enhanced the productivity in a great manner

The Information as a Service has the examples as below –

• The payment processing being carried out wherein the customers of the organizations pay for the products or the services that they utilize

• The Validation and Lookup Functioning of the Zip Codes of the various customers that are associated to the organization

• The use of the grouping of data as is required for the data analytics functionality within the organization

The Analytics as a Service has the examples as below –

• The remote analytics which are provided to the stakeholders of the organization

• The use of the analytics software in the consideration of the sales category

• The use of the driving of the marketing campaigns within the organization

References

Almunawar, M. N., Islam, M. Z., & de Pablos, P. O. (Eds.). (2022). Digitalisation and Organisation Design: Knowledge Management in the Asian Digital Economy. Routledge.

Demir, A., Budur, T., Omer, H. M., & Heshmati, A. (2021). Links between knowledge management and organisational sustainability: does the ISO 9001 certification have an effect?. Knowledge Management Research & Practice, 1-14.

Masood, T., Cherifi, C. B., & Moalla, N. (2021). A machine learning approach for performance-oriented decision support in service-oriented architectures. Journal of Intelligent Information Systems, 56(2), 255-277.

Moreira, M. W., Rodrigues, J. J., Sangaiah, A. K., Al-Muhtadi, J., & Korotaev, V. (2018). Semantic interoperability and pattern classification for a service-oriented architecture in pregnancy care. Future Generation Computer Systems, 89, 137-147.

North, K., & Kumta, G. (2018). Knowledge management: Value creation through organizational learning. Springer.

Vassakis, K., Petrakis, E., & Kopanakis, I. (2018). Big data analytics: applications, prospects and challenges. In Mobile big data (pp. 3-20). Springer, Cham.

Wang, Y., & Xu, W. (2018). Leveraging deep learning with LDA-based text analytics to detect automobile insurance fraud. Decision Support Systems, 105, 87-95.