Data Mining and Visualization For Intelligence- myassignmenthelp

Question: Discuss about theData Mining and Visualization For Business Intelligence. Answer: Introduction In Business, privacy goes to the extent of protecting the data and information of a customer, which are both sensitive and confidential. It makes sure that the IT systems are in compliance with present privacy policy of the organization. The most crucial part in business is privacy and thus the organizations must understand and know the means of this privacy concern. Data mining delivers a vital role in the competitive advantages of an organization. In the data storage system the data mining techniques has become crucial and there has been a potential use of data mining in this field. Data Mining was introduced in the year 1990. It was basically done for the extraction of hidden information. Data mining is all about data quality, privacy and security measure. It enhances the competitiveness of an organization. Data mining helps in Decision making, Data Presentation, Data Mining, Data Exploring, Data Preprocessing, Warehousing and Data sources. Data Mining in Business Data Mining is the technique in which the company turns raw data and information into useful information. By data mining in business, the organization can know more about their customer and develop more effective marketing strategy. It basically depends on the computer processing, data collection and data warehousing (George, Kumar Kumar 2015). This helps in keeping track of the customers buying record in the retail shops or in super markets, which helps in decision making process of the customers liking and disliking and the marketing technique of the shop. Data mining can be a cause for concern to prove certain hypothesis. Summarizing in brief - Use of Data Mining in Business The Data Mining is generally used to find the relationship and pattern that helps in making better decisions in Business. This helps in determining and sorting the sales, trends and for develops campaigns for smart marketing and hence predicts the loyalty toward the product of the customers. The Role of Data Mining in Business Optimization is that Data Mining helps to provide competitive advantages in business. There are six primary techniques of Data Mining to analyze data: Classification, Regression, Clustering, Association Rule Learning, Anomaly Detection and Summarization. There are three main areas where data mining is applied successfully: Retail, Banking and Insurance (Imtiyaj 2015). In Retail helps in improving the quality and costing of the services, achieves better customer retention and satisfaction, enhancing good consumption ratios, designing effective products, distributive policies and transporting. In Banking the data mining includes segmentation of customers, profitability, and credit analysis, marketing, predicting payment defaults, and transaction, even investment ranking, portfolios optimizing, cash management and forecasting operations. Credit scoring, Customer segmentation and Customer profitability are the main examples of this sector. In Insurance there are applications like fraud detecting, retaining, risk factors identification and many more (Kasemsap 2015). Article related to Data Mining in Business The article has been chosen An Advanced Inventory Data Mining System for Business Intelligence. By Q Zhou, B Xia, W Xue, C Zeng, R Han and T Li explaining the iMiners, that have been developed for intelligent management system. From demand-drive the inventory management system is improved to data-driven and hence addresses the challenges for complex transaction process and Big Data. Conclusion Increase in data resources tends to drive a growth in business analytics and thus data mining. Businesses are getting to realize the application of data mining with the competitive edge. Business Intelligence and Data Mining works hand in hand for the development of knowledge based industry. References George, J., Kumar, V., Kumar, S. (2015). Data Warehouse Design Considerations for a Healthcare Business Intelligence System. InWorld Congress on Engineering. Imtiyaj, S. (2015). Privacy Preserving Data Mining.transactions,2(2). Kasemsap, K. (2015). The role of data mining for business intelligence in knowledge management.Integration of data mining in business intelligence systems, 12-33. Zhou, Q., Xia, B., Xue, W., Zeng, C., Han, R., Li, T. An Advanced Inventory Data Mining System for Business Intelligence.