detection but will not release it or use it for any other purpose. DATE: 06/10/2013 Introduction: In data mining it is said that “success or failure often depends not only on how well you are able to collect data but also on how well you are able to convert them into knowledge that will help you better manage your business (Wilson‚ 2001‚ p. 26).” Tourism and hospitality industry generates massive amount of data. In each and every transaction there is set of data generated. In tourism and hospitality
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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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Case Study Italian retailer Unicomm selects Huawei RH5885 V2 server for its SAP HANA database and S7700 and S5700 switches. Huawei’s SAP HANA application came about as a result of a successful switching project and helps Unicomm to analyse sales data in real time. “With the SAP HANA solution‚ we needed a partner that was ready to support us in every way possible. By helping us to stay in budget and to adopt a system that could grow in line with company requirements‚ Huawei really delivered.” Federico
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Crime Data Comparison Comparing similar crimes‚ in metropolitan area such as Phoenix and Dallas. The FBI Uniform Crime Report (UCR) data shows in 2009 Phoenix had 76 reported murders‚ and Dallas with 86. Dallas with a lower population number of 1‚290‚266 had higher murder rate‚ Phoenix with population of 1‚597‚397 reported in 2009. Reported murder rates dropped in both areas in 2010‚ Dallas with 73‚ and Phoenix with a reported 50. “National reports a decrease of 6.2 percent of violent crimes during
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DATA ORGANIZATION‚ PRESENTATION AND ANALYSIS Research Methods 1 Data Organization and Presentation To make interpretation and analysis of gathered data easier‚ data should be organized and presented properly. The usual methods used by researchers are textual‚ tables‚ graphs and charts. 1.1 Textual Data can be presented in the form of texts‚ phrases or paragraphs. It involves enumerating important characteristics‚ emphasizing significant figures and identifying important features of
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000041692______ mm 110 kilometers = _____110000_____ m = ____110000000________ mm 3.7 hectometers =____370_____ m =_____37000_______ cm 451‚000‚000 μm = ____.000451_____ m = ____.0000451_______ dam 2) Imagine a field is about 100 meters long. If you run a 5K race how many meters is it? Approximately how many “fields” does this equate to? 50 football fields 3) Measure the following objects. A) Your computer screen (in meters) Length______________ Width ______________ Area _______________
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Data Anomalies Normalization is the process of splitting relations into well-structured relations that allow users to inset‚ delete‚ and update tuples without introducing database inconsistencies. Without normalization many problems can occur when trying to load an integrated conceptual model into the DBMS. These problems arise from relations that are generated directly from user views are called anomalies. There are three types of anomalies: update‚ deletion and insertion anomalies. An update anomaly
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Queenie 1097300104 E5B Data Analysis First Part Personal information: including the participants’ gender‚ age‚ educational background‚ marital status and monthly income. Gender As Figure 1 showed‚ there were 45% of female participants and 55% of male. The numbers of the participants of each gender were very close. Age The respondents were all my friends on Facebook; as the result‚ the majority (73%) of their age was in the range of 16-20‚ as seen in Figure 2. Figure 1: Gender
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EE2410: Data Structures Cheng-Wen Wu Spring 2000 cww@ee.nthu.edu.tw http://larc.ee.nthu.edu.tw/˜cww/n/241 Class Hours: W5W6R6 (Rm 208‚ EECS Bldg) Requirements The prerequites for the course are EE 2310 & EE 2320‚ i.e.‚ Computer Programming (I) & (II). I assume that you have been familiar with the C programming language. Knowing at least one of C++ and Java is recommended. Course Contents 1. Introduction to algorithms [W.5‚S.2] 2. Recursion [W.7‚S.14] 3. Elementary data structures: stacks‚ queues
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am going to explain data protection‚ talk about the data protection acts‚ rights and principles. I’m going to talk about a data controller and a data processor and what their responsibilities are. What personal and sensitive data are. What a data receiver is and what his rights are‚ what is involved in direct marketing and I will mention an example of abuse or corruption that occurred in Ireland. Data protection acts Data protection is legal control over and access to use of data stored in computers
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