Data Mining On Medical Domain Smita Malik‚ Karishma Naik‚ Archa Ghodge‚ Shivani Gaunker Shree Rayeshwar Institute of Engineering & Information Technology Shiroda‚ Goa‚ India. Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com Abstract-The successful application of data mining in highly visible fields like retail‚ marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries
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DATA INTEGRATION Data integration involves combining data residing in different sources and providing users with a unified view of these data. This process becomes significant in a variety of situations‚ which include both commercial (when two similar companies need to merge their databases and scientific (combining research results from different bioinformatics repositories‚ for example) domains. Data integration appears with increasing frequency as the volume and the need to share existing data explodes
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Customer loyalty and customer satisfaction Customer Loyalty can be difficult to define given the different views that are presented within the literature. Zithaml‚ Berry and Parasuraman (1996) determine that loyalty includes a customer’s intention to stay with an organisation and that loyalty includes four elements: repurchase intentions‚ recommending the service provider to other customers‚ less complaints and tolerance of price increases. Oliver‚ (1999) provides a different definition and
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Big Data Management: Possibilities and Challenges The term big data describes the volumes of data generated by an enterprise‚ including Web-browsing trails‚ point-of-sale data‚ ATM records‚ and other customer information generated within an organization (Levine‚ 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations‚
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Q) What are Secondary Data? Secondary Data Secondary data is information gathered for purposes other than the completion of a research project. Data previously collected by someone else‚ possibly for some other purpose that can be used later for making decisions if found suitable for the purpose‚ other than the original one. Secondary data can be acquired from the internal records of the organization‚ their departments‚ subsidiaries or sister organizations and also from external sources‚ such
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Handling Consumer Data Introduction When I visit my local Caltex Woolworths petrol station on “cheap fuel Wednesday” to cash in the 8c per litre credit that my Wife earned the previous Friday buying the groceries with our “Everyday Rewards” card‚ I did not‚ until researching this report‚ have any clue as to the contribution I was making to a database of frightening proportions and possibilities… nor that‚ when I also “decide” to pick up the on-sale‚ strategically-placed 600mL choc-milk‚ I am
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number of articles on “big data”. Examine the subject and discuss how it is relevant to companies like Tesco. Introduction to Big Data In 2012‚ the concept of ‘Big Data’ became widely debated issue as we now live in the information and Internet based era where everyday up to 2.5 Exabyte (=1 billion GB) of data were created‚ and the number is doubling every 40 months (Brynjolfsson & McAfee‚ 2012). According to a recent research from IBM (2012)‚ 90 percent of the data in the world has been
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Electronic copy available at: http://ssrn.com/abstract=2185653 1 A TAXONOMY OF INTELLECTUAL CAPITAL: 2006-2009 POLISH BANKS PERSPECTIVE Karol Śledzik* University of Gdansk Faculty of Management Department of Banking ul. Armii Krajowej 101 81-824 Sopot‚ POLAND ABSTRACT The main goal of this paper is to present practical application of taxonomy (Multidimensional Comparative Analysis - MCA) to measure the level of intellectual capital of banks using VAIC™ (Value Added of Intellectual Coefficient)
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“EFFECTIVENESS OF CUSTOMER RELATIONSHIP MANAGEMENT PROGRAMME IN STATE BANK OF INDIA” Submitted In The Partial Fulfillment Of Degree Of MBA Batch 2006-08 SUBMITTED TO: - SUBMITTED BY:- Mrs. Riya Sharma Rishi Gupta (Project Guide) Roll no. 0471483906 [pic] MAHARAJA AGRASEN INSTITUE OF TECHNOLOGY PSP AREA‚ SECTOR-22 ROHINI‚ DELHI—110085 Ph: 25489493- WHOM
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Data Mining DeMarcus Montgomery Dr. Janet Durgin CIS 500 June 9‚ 2013 Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model‚ which has‚ in turn been trained over your data‚ learning from the experience
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