CHAPTER ONE INTRODUCTION 1.1 BACKGROUND OF THE STUDY Indeed‚ accountancy profession is a profession that encompasses other profession and that is why accounting has usually been thought of as highly technical field that can only be understood by the professionals (chartered accountants). Also‚ it has often been called ‘the language of business. Even‚ people in the business world owners‚ managers‚ banks‚ stockbrokers‚ investors‚ human resource managers‚ lawyers‚ to mention a few all uses
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A glimpse of Big Data Jan. 2013 What is big data? “Big data is not a precise term; rather it’s a characterization of the never ending accumulation of all kinds of data‚ most of it unstructured. It describes data sets that are growing exponentially and that are too large‚ too raw or too unstructured for analysis using relational database techniques. Whether terabytes or petabytes‚ the precise amount is less the issue than where the data ends up and how it is used.”------Cite from EMC’s report
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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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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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1 Secondary data analysis: an introduction All data are the consequence of one person asking questions of someone else. (Jacob 1984: 43) This chapter introduces the field of secondary data analysis. It begins by considering what it is that we mean by secondary data analysis‚ before describing the type of data that might lend itself to secondary analysis and the ways in which the approach has developed as a research tool in social and educational research. The second part of the chapter considers
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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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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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2 Areas of data processing 1. Business Data processing (BDP) . Business data processing is characterized by the need to establish‚ retain‚ and process files of data for producing useful information. Generally‚ it involves a large volume of input data‚ limited arithmetical operations‚ and a relatively large volume of output. For example‚ a large retail store must maintain a record for each customer who purchases on account‚ update the balance owned on each account‚ and a periodically present a
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TYPES OF DATA AND COMPONENTS OF DATA STRUCTURES Data types 1. Primitive: is a data type provided by a programming language as a basic building block 2. Composite: is any data type which can be constructed in a program using its programming language’s primitive data types and other composite types 3. Abstract: is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics
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4. Assurance on CSR/Sustainability reporting a) In recent years there have been a growing number of organisations voluntarily reporting on their non-financial performance. KPMG’s International Survey of Corporate Responsibility (2011: 6) found that: ‘95% of the 250 largest companies in the world (G250 companies) now report on their corporate responsibility (CR) activities‚ 66% of non-reporters are based in the US.’ There has been a growing trend in companies (especially in Europe) wanting to
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