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    Data Mining

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    Chapter 1 Exercises 1. What is data mining? In your answer‚ address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead‚ the 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. Thus‚ data mining can be viewed as the result of

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    Data Types

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    a methodology for constructing the dynamic execution graph that characterizes the execution of an ordinary program (an application program written in an imperative language such as C or FORTRAN) from a serial execution trace of the program. It then uses the methodology to study parallelism in the SPEC benchmarks. We see that the parallelism can be bursty in nature (periods of lots of parallelism followed by periods of little parallelism)‚ but the average parallelism is quite high‚ ranging from 13

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    Data Migration

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    Data migration • Data migration is the process of transferring data between storage types‚ formats‚ or computer systems. • Data migration is usually performed programmatically to achieve an automated migration‚ freeing up human resources from tedious tasks. • It is required when organizations or individuals change computer systems or upgrade to new systems. • To achieve an effective data migration procedure‚ data on the old system is mapped to the new system providing a design

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    data gathering

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    Summary of data gathering There are more cars and trucks going through the intersection of Spring Street and Route 27 in the morning than the afternoon. How to determine cars and trucks Cars are usually used for taking passengers to the destination; in general‚ they are smaller than trucks. As for trucks‚ there are larger spaces to carry items‚ for example‚ gasoline‚ foods‚ and other goods. In addition‚ school buses are important transportations on campus‚ but they are counted as neither cars

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    Data Structure

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    Module 815 Data Structures Using C M. Campbell © 1993 Deakin University Module 815 Data Structures Using C Aim After working through this module you should be able to create and use new and complex data types within C programs. Learning objectives After working through this module you should be able to: 1. Manipulate character strings in C programs. 2. Declare and manipulate single and multi-dimensional arrays of the C data types. 3. Create‚ manipulate and manage C pointers

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    data protection

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    ict policy Data Protection ICT/DPP/2010/10/01   1. Policy Statement 1.1. Epping Forest District Council is fully committed to compliance with the requirements of the Data Protection Act 1998 which came into force on the 1st March 2000. 1.2. The council will therefore follow procedures that aim to ensure that all employees‚ elected members‚ contractors‚ agents‚ consultants‚ partners or other servants of the council who have access to any personal data held by or on behalf of the

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    Data Collected

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    Stages of Economic Integration: From Autarky to Economic Union As international trade and investment levels continue to rise‚ the level of economic integration between various groups of nations is also deepening.  The most obvious example of this is the European Union‚ which has evolved from a collection of autarkical nations to become a fully integrated economic unit.  Although it is rare that relationships between countries follow so precise a pattern‚ formal economic integration takes place

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    Big DATA

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    4V of Big Data? Imagine all the information you alone generate each time you swipe your credit card‚ post to social media‚ drive your car‚ leave a voicemail‚ or visit a doctor. Now try to imagine your data combined with the data of all humans‚ corporations‚ and organizations in the world! From healthcare to social media‚ from business to the auto industry‚ humans are now creating more data than ever before. volume‚ velocity‚ variety‚ and veracity. Volume: Scale of Data Big data is big. It’s

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    Payroll Data

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    into the Workers’ Compensation (WC) actuarial model workbook. Payroll data for the WC model should contain “only the actual hours worked” for specific Rate Schedule Codes (RSC) groups‚ including executives. The WC payroll data should exclude all paid leave types. A comparison of work hours from the NPHRS mainframe report to the summary in EDW reveals very small differences. We hope to align the NPHRS and EDW work hour data. Also‚ we (Technical Analysis‚ Accounting and Finance) need to understand

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    data communications

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    CHAPTER 12 ROUTING IN SWITCHED NETWORKS A NSWERS TO Q UESTIONS 12.1 The average load expected over the course of the busiest hour of use during the course of a day. 12.2 The tradeoff is between efficiency and resilience. 12.3 A static routing strategy does not adapt to changing conditions on the network but uses a fixed strategy developed ahead of time. With alternate routing‚ there are a number of alternate routes between source and destination and a dynamic choice of routes is

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