"Distinguish between primary data and secondry data" Essays and Research Papers

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    Data Masking

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    An Oracle White Paper July 2010 Data Masking Best Practices Oracle White Paper—Data Masking Best Practices Executive Overview ........................................................................... 1 Introduction ....................................................................................... 1 The Challenges of Masking Data ....................................................... 2 Implementing Data Masking .............................................................. 2

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    Secondary Data

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    Collecting‚ Reviewing‚ and Analyzing Secondary Data WHAT IS SECONDARY DATA REVIEW AND ANALYSIS? Secondary data analysis can be literally defined as second-hand analysis. It is the analysis of data or information that was either gathered by someone else (e.g.‚ researchers‚ institutions‚ other NGOs‚ etc.) or for some other purpose than the one currently being considered‚ or often a combination of the two (Cnossen 1997). If secondary research and data analysis is undertaken with care and diligence

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    Secondary data

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    Secondary data refers to the data which an investigator does not collect himself for his purpose rather he obtains them from some other source‚ agency or office. In other words‚ this data has already been collected by some other source and an investigator makes use of it for his purpose. Secondary data is different from primary data on the basis of the sources of their collection. The difference between the two is relative - data which is primary at one place become secondary at another place.

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    Data Mining

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    Stock Exchange forecasting with Data Mining and Text Mining (Marketing and Sales Analysis) Full names : Fahed Yoseph TITLE : Senior software and Database Consultatnt (Founder of Info Technology System) E-mail: Yoseph@info-technology.net Date of submission: Sep 15th of 2013 CONTENTS PAGE Chapter 1 1. ABSTRACT 2 2. INTRODUCTION 3 2.1 The research problem. 4 2.2 The objectives of the proposal. 4 2.3 The Stock Market movement. 5 2.4 Research question(s). 6 2. Background 3. Problem

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    Data Process

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    Data Processing All through the different stages in civilization‚ man has always tried to look for ways to simplify work and to solve problems more efficiently. Many problems involved numbers and quantities‚ so man started looking for easier ways to count‚ to add‚ subtract‚ multiply and divide. As society has grown in both size and complexity‚ so have data that are generated by it through time. Definition of Terms Data – is defined as any collection of facts. Thus sales reports‚ inventory

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    DATA COLLECTION

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    DATA COLLECTION Business Statistics Math 122a DLSU-D Source: Elementary Statistics (Reyes‚ Saren) Methods of Data Collection 1. 2. 3. 4. 5. DIRECT or INTERVIEW METHOD INDIRECT or QUESTIONNAIRE METHOD REGISTRATION METHOD OBSERVATION METHOD EXPERIMENT METHOD DIRECT or INTERVIEW Use at least two (2) persons – an INTERVIEWER & an INTERVIEWEE/S – exchanging information.  Gives us precise & consistent information because clarifications can be made.  Questions not fully understood by the respondent

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    Data Migration

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    Department of Education Office of Federal Student Aid Data Migration Roadmap: A Best Practice Summary Version 1.0 Final Draft April 2007 Data Migration Roadmap Table of Contents Table of Contents Executive Summary ................................................................................................................ 1 1.0 Introduction ......................................................................................................................... 3 1.1 1.2 1.3 1.4 Background

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    Data Replication

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    Outline  Introduction  Distributed DBMS Architecture  Distributed Database Design  Distributed Query Processing  Distributed Transaction Management  Data Replication  Consistency criteria  Update propagation protocols  Parallel Database Systems  Data Integration Systems  Web Search/Querying  Peer-to-Peer Data Management  Data Stream Management Distributed & Parallel DBMS M. Tamer Özsu Page 6.1 Acknowledgements  Many of these slides are from notes prepared by  Prof. Gustavo

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    Data Modeling

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    Lecture Notes 1 Data Modeling ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova‚ MSIT 1 • Database: A collection of related data. • Data: Known facts that can be recorded and have an implicit meaning. – An integrated collection of more-or-less permanent data. • Mini-world: Some part of the real world about which data is stored in a database. For example‚ student grades and transcripts at a university. • Database Management System (DBMS): A software package/ system to facilitate

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    Big Data

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    .......................................................................................... 3 2.1.2 Non-functional requirement ............................................................................................. 5 3. Logical design: Data Modeling (ERD) .................................................................................... 6 4. Logical design: Process Modeling (DFD) ............................................................................... 9 5. Decision

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