BOC-008-0312/2007 DATA COLLECTION METHODS Methods of data collection. The term data means groups of information that represent the qualitative or quantitative attributes of a variable or set of variables. Data are typically the results of measurements and can be the basis of graphs‚ images‚ or observations of a set of variables. Data are often viewed as the lowest level of abstraction from which information and knowledge are derived. Data can be classified into primary and secondary data. In order to
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The Evolution of Data Models The quest for better data management has led to different models that attempt to resolve the file system’s critical shortcomings. Because each data model evolved from its predecessors‚ it is essential to examine the major data models in roughly chronological order. 1.1 The Hierarchical Model A Hierarchical Database Model is a data model in which the data is organized into a tree-like structure. The structure allows representing information using parent/child relationships:
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Electronic Data Interchange * Electronic data interchange (EDI) is the structured transmission of data between organizations by electronic means‚ which is used to transfer electronic documents or business data from one computer system to another computer system‚ i.e. from one trading partner to another trading partner without human intervention. It is more than mere e-mail; for instance‚ organizations might replace bills of lading and even cheques with appropriate EDI messages. It also refers
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Data warehousing and OLAP Swati Vitkar Research Scholar‚ JJT University‚ Rajasthan. Abstract: Data warehousing and on-line analytical processing (OLAP) are essential elements of decision support‚ which has increasingly become a focus of the database industry. Many commercial products and services are now available‚ and all of the principal database management system vendors now have offerings in these areas. Decision support places some rather different requirements on database technology compared
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broadcast radio and cable television * Channel allocated even if no data Frequency Division Multiplexing Diagram * Each signal is modulated to a different carrier frequency * Carrier frequencies separated by guard bands (unused bandwidth) – to prevent interference so signals do not overlap. 3 FDM System FDM is an analog multiplexing technique that combines signals. FDM process FDM Demultiplexing Example 1 Assume that a voice channel occupies a bandwidth of 4 KHz. We need
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METHODS OF DATA COLLECTION BY ADEDOYIN SAMUEL ADEBAYO INTERNATIONAL BLACK SEA UNIVERSITY TBILISI - GEORGIA MA IN EDUCATION STUDENT NO:12500151 LECTURER: PROF. IRINA BAKHTADZE METHODS OF COLLECTING DATA Introduction: Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. Data collection methods for impact evaluation vary along a continuum. At the one end
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SAP DATA ARCHIVING INDEX 1. Introduction................................................................................................... 2. Archiving Objects......................................................................................... 2.1 Definition..................................................................................................................................... 2.2 Archiving objects and related tables................
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1. PRIMARY ANDSECONDARY DATA We explore the availability and use of data (primary and secondary) in the field of business research.Specifically‚ we examine an international sample of doctoral dissertations since 1998‚ categorizingresearch topics‚ data collection‚ and availability of data. Findings suggest that use of only primarydata pervades the discipline‚ despite strong methodological reasons to augment with secondary data. INTRODUCTION Data can be defined as the quantitative or qualitative
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Data & Knowledge Engineering Introduction Database Systems and Knowledgebase Systems share many common principles. Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKEreaches a world-wide audience of researchers‚ designers‚ managers and users. The major aim of the journal is to identify‚ investigate and analyze the underlying principles in the design and effective use of these systems.DKE achieves this aim
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http://hdl.handle.net/2451/31553 Data Science and Prediction Vasant Dhar Professor‚ Stern School of Business Director‚ Center for Digital Economy Research March 29‚ 2012 Abstract The use of the term “Data Science” is becoming increasingly common along with “Big Data.” What does Data Science mean? Is there something unique about it? What skills should a “data scientist” possess to be productive in the emerging digital age characterized by a deluge of data? What are the implications for business
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