Business Information System Data Mining

Question: Discuss about theBusiness Information Systemfor Data Mining. Answer: Data Mining: Data mining is defined as the process of analyzing data from several perspectives as well as summarizing it into making successful information that can be utilized in order to increase revenue and minimize the costs (Witten et al. 016). In other words, data mining is the procedure of sorting data through data sets in order to identify the patterns and develop relations for solving the issues through data analysis. The tools of data mining enterprises make prediction of future trends. Applications of Data Mining: Larose (014) stated that data mining is generally used today by the organization having a strong focus to the customers of retail, communication as well as marketing in order to drill down into transactional data as well as determine pricing along with preferences of customers. Future healthcare: One of the applications of data mining is its uses in future health care. It holds great potential for enhancing the health system. It utilizes data as well as analytics to detect best approaches that enhance care and minimize costs (Wu et al. 014). The approaches of data mining such as multi-dimensional databases and machine learning as well as soft computing are used by the researchers. Manufacturing engineering: Rokach and Maimon (014) commented that knowledge is one of the best assets of a manufacturing organization. Data mining tools are very useful for discovering the patterns in the complex procedure of manufacturing. In addition, data mining is the process of system-level designing in order to extract relationships between architecture of product in order to predict development of the product, cost and span time as well as dependencies among the tasks. Customer relationship management: It deals with acquiring as well as retaining of the customers along with improving loyalty of the customers. Data mining technologies are helpful to collect data that can be used for analysis. Moreover, it is important to maintain appropriate relationship with the customers in business (Braha 013). It is required to gather data and analyze the information. The data mining technologies are useful to retain customer and provide filtered solution. Major Elements of Data Mining: Freitas (013) stated that there are five major elements of data mining those have important roles in using the data mining technologies. Extract, transform as well as load transaction of the system of data warehouse. Storing as well as managing of data in multi-dimensional system is one of the most important components of data mining. In addition, providing data access to the analytics of business as well as professionals of information technology and analyzing the data by the application of software is considered as vital elements of data mining system. Presenting of data in useful format like graph and chart is one of the major elements of data mining. Examples of Each Element: The elements of data mining are used in applying the statistics as well as data mining against the whole database. The business users are generally depended on administrators and developers in order to apply analytical function against specific set of data. On the other hand, plug-and-play architecture for the functions of custom analysis is used by several organizations that have specific calculations required as unique as well as proprietary character of the business model is involved in it. In addition, seamless integration with the data mining tools has main purpose to discover the patterns as well as embed them in BI report and analysis (Lin et al. 013). Collaboration technology is used as statistical analysis as well as data mining tool that needs to operate collaboratively with engines of calculation embedded in relational database management system. Multi-pass SQL has several normal business questions that any user of business likes to constrain through the limits of tool tha t cannot be answered by single-pass SQL. Issues with Data Mining: There are several advantages of using data mining technology in various sector of business. However, some limitations of data mining need to be minimized in the usage. The issues can be described as followed. Braha (013) asserted that several types of mining as well as new kinds of knowledge, knowledge of mining in multi-dimensional space and data mining in interdisciplinary effort. In addition, efficiency as well as scalability in data mining algorithm is one of the major issues of data mining. Presentation and visualization of the data mining results several issues while using the technology. Handling of relational as well as complex types of data and handling noise as well as incompleteness of data are major issues related with data mining. Moreover, interactive mining of knowledge in different way is one of the issues faced while implementing data mining technology. Data mining query languages as well as ad hoc data mining, high level query language of data mining is a major issue of data mining. Hence, it is required to take proper actions in order to overcome the issues faced for using data mining. In the specified website, 816 accounts related jobs are available. Name of the qualification Greatest number of jobs 1. Trades Service 14,90 . Information Communication Technology 14,099 3. Healthcare Medical 11,767 4. Manufacturing, Transport Logistics 9,958 5. Sales 8,488 6. Accounting 8,16 7. Administration Office Support 7,546 8. Construction 7,478 9. Hospitality Tourism 7,355 10. Retail Consumer Products 5,93 From the above table, it is observed that the number of jobs is 14,90 in Trades Service, which is greatest than others. In Information Communication Technology has second highest number of jobs that is 14,099 (Seek.com.au 017). Health Medical includes 9,958 numbers of jobs. On the other hand, Sales section includes 8,488 jobs, Accounting has 8,16 jobs, Administration Office Support has 7,546 jobs, Construction has 7,478 jobs, Hospitality Tourism has 7,355 jobs listed and Retail Consumer Products has 5,93 number of jobs recorded in the site. Pay Categories Number of jobs $30k-$40k 7031 jobs $40k-$50k 5,77 jobs $50k-$60k 39,090 jobs $60k-$70k 34,333 jobs References Braha, D. (Ed.). (013).Data mining for design and manufacturing: methods and applications(Vol. 3). Springer Science and Business Media. Freitas, A. A. (013).Data mining and knowledge discovery with evolutionary algorithms. Springer Science and Business Media. Larose, D. T. (014).Discovering knowledge in data: an introduction to data mining. John Wiley and Sons. Lin, T. Y., Yao, Y. Y., and Zadeh, L. A. (Eds.). (013).Data mining, rough sets and granular computing(Vol. 95). Physica. Rokach, L., and Maimon, O. (014).Data mining with decision trees: theory and applications. World scientific. Seek.com.au. (017).SEEK - Australia's no. 1 jobs, employment, career and recruitment site. Available at: https://www.seek.com.au/ [Accessed 10 Apr. 017]. Witten, I. H., Frank, E., Hall, M. A., and Pal, C. J. (016).Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann. Wu, X., Zhu, X., Wu, G. Q., and Ding, W. (014). Data mining with big data.ieee transactions on knowledge and data engineering,6(1), 97-107.