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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Big Data‚ Data Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse
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Definition: Statistics is the study of the collection‚ organization‚ analysis‚ interpretation and presentation of data. It deals with all aspects of this‚ including the planning of data collection in terms of the design of surveys and experiments. A statistician is someone who is particularly well-versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained experience through working in any of a wide number of fields. Some
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A data mining approach to analysis and prediction of movie ratings M. Saraee‚ S. White & J. Eccleston University of Salford‚ England Abstract This paper details our analysis of the Internet Movie Database (IMDb)‚ a free‚ user-maintained‚ online resource of production details for over 390‚000 movies‚ television series and video games‚ which contains information such as title‚ genre‚ box-office taking‚ cast credits and user ’s ratings. We gather a series of interesting facts and relationships
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Support Spatial Data Mining Gennady Andrienko and Natalia Andrienko GMD - German National Research Center for Information Technology Schloss Birlinghoven‚ Sankt-Augustin‚ D-53754 Germany gennady.andrienko@gmd.de http://allanon.gmd.de/and/ Abstract. Data mining methods are designed for revealing significant relationships and regularities in data collections. Regarding spatially referenced data‚ analysis by means of data mining can be aptly complemented by visual exploration of the data presented on
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Abstract Data mining is one of the most important tools for analyzing information from large databases. The retail industry has recently seen the growing number of data mining applications in reducing time and cost for the industry. The paper defines data mining and the seven operations of data mining that have been classified through many different literatures. It then focus on the important applications of data mining in retail industry including marketing‚ customer relationship management‚ risk
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An Oracle White Paper July 2010 Data Masking Best Practices Oracle White Paper—Data Masking Best Practices Executive Overview ........................................................................... 1 Introduction ....................................................................................... 1 The Challenges of Masking Data ....................................................... 2 Implementing Data Masking .............................................................. 2
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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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DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm
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DATA COLLECTION Business Statistics Math 122a DLSU-D Source: Elementary Statistics (Reyes‚ Saren) Methods of Data Collection 1. 2. 3. 4. 5. DIRECT or INTERVIEW METHOD INDIRECT or QUESTIONNAIRE METHOD REGISTRATION METHOD OBSERVATION METHOD EXPERIMENT METHOD DIRECT or INTERVIEW Use at least two (2) persons – an INTERVIEWER & an INTERVIEWEE/S – exchanging information. Gives us precise & consistent information because clarifications can be made. Questions not fully understood by the respondent
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