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    Chapter 9 Property Acquisition and Cost Recovery SOLUTIONS MANUAL Problems 39. [LO 1] Jose purchased a delivery van for his business through an online auction. His winning bid for the van was $24‚500. In addition‚ Jose incurred the following expenses before using the van: shipping costs of $650; paint to match the other fleet vehicles at a cost of $1‚000; registration costs of $3‚200 which included $3‚000 of sales tax and a registration fee of $200; wash and detailing for $50; and an engine

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    Big Data

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    Big DataData 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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    Customer Data

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    CUSTOMER DATA In the term of customer data‚ technology now day give a big role to evaluate the concepts by the overall to moving ownership of the customer when they are away from the individual departments and different it at the enterprise level. In the customer relationship management concept‚ individual that in the each department has responsible for the customer. The success factor for Customer Relationship Management (CRM) is by deploying technology that provides various levels of data access

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    Big Data

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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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    Data Mining

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    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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    Big Data

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    billion bytes of data in digital form be it on social media‚ blogs‚ purchase transaction record‚ purchasing pattern of middle class families‚ amount of waste generated in a city‚ no. of road accidents on a particular highways‚ data generated by meteorological department etc. This huge size of data generated is known as big data. Generally managers use data to arrive at decision. Marketers use data analytics to determine customer preferences and their purchasing pattern. Big data has tremendous potential

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    data mining

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    Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific

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    data mining

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    Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed

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    DATA ORGANIZATION

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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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    Data Dictionary

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    DATA DICTIONARY Data Dictionaries‚ a brief explanation Data dictionaries are how we organize all the data that we have into information. We will define what our data means‚ what type of data it is‚ how we can use it‚ and perhaps how it is related to other data. Basically this is a process in transforming the data ‘18’ or ‘TcM’ into age or username‚ because if we are presented with the data ‘18’‚ that can mean a lot of things… it can be an age‚ a prefix or a suffix of a telephone number‚ or basically

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