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    Data Collection Methods

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    Factors that influence the selection of data collection instruments 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 of this continuum are quantitative methods and at the other end of the continuum are Qualitative methods for data collection. A data collection instrument is a tool for monitoring

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    data collection methods

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    Data Collection Methods. Introduction Data collection is the process of gathering and measuring information on variables of interest‚ in an established systematic fashion that enables one to answer stated research questions‚ test hypotheses‚ and evaluate outcomes. Data Collection Techniques include the following: Personal Interviews Conducting personal interviews is probably the best method of data collection to gain first hand information. It is however‚ unsuitable in cases where there are

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    Report on Data Management

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    Activity 1 Report on Data Management Contents Page Title Page(s) Introduction 4 Why Collect HR Data 4 Types of HR Data and how it supports HR 4 Data Storage and its Benefits 5 Essential UK legislations relating to recording‚ storing and accessing HR data 5-6 Conclusion 6 Reference List 7 Introduction HR data would need to be stored by all organisations due to either legal requirements or internal purposes. This report will uncover

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    Ibm Big Data

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    era of big data Manage‚ optimize and increase availability of your IBM DB2 for Linux‚ UNIX and Windows database and applications— delivering valuable intelligence to help your business users make informed decisions‚ fast Database management solutions for the era of big data 1 Introduction Accelerate development 2 Optimize performance 3 4 Increase availability 5 Give your business a competitive edge Database management solutions for the era of big data Introduction

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    Fig: Architecture of data warehouse Operations Conceiving data as a cube with hierarchical dimensions leads to conceptually straightforward operations to facilitate analysis. Aligning the data content with a familiar visualization enhances analyst learning and productivity.[5] The user-initiated process of navigating by calling for page displays interactively‚ through the specification of slices via rotations and drill down/up is sometimes called "slice and dice". Common operations

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    Data‚ Information‚ and Knowledge – Interwoven To explore the concepts of Data‚ Information‚ and Knowledge independently is to attempt building a large and complex puzzle with only a few pieces from the box. While the relationships between these concepts can be as elusive as finding their universal definitions‚ it is within these relationships that data‚ information‚ and knowledge are most meaningful. In the broadest sense‚ data exists in the form of unorganized and raw facts about the environment

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    Traffic Data Collection

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    EXERCISE 1 TRAFFIC DATA COLLECTION AND PRESENTATION CE 5203 TRAFFIC FLOW AND CONTROL ADITYA NUGROHO HT083276E DEPARTMENT OF CIVIL ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2010 Department of Civil Engineering CE 5203 Traffic Flow and Control 1.0 INTRODUCTION The measurement of traffic volumes is one of the most basic functions of highway planning and management. Traffic counting can include volume‚ direction of travel‚ vehicle classification‚ speed‚ and lane position. In this

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    BIG DATA ANALYTICS

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    Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture‚ curation‚ storage search‚ sharing‚ transfer‚ analysis and visualization. At multiple TERABYTES in size‚ the text and images of Wikipedia are a classic example of big data. As of 2012‚ limits on the size of data sets that

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    1. With necessary diagram explain about data warehouse development life cycle . Ans : Introduction to data warehouses. Data warehouse development lifecycle (Kimball’s approach) Q. 2. What is Metadata ? What is it’s uses in Data warehousing Archietechture ? Ans : In simple terms‚ meta data is information about data and is critical for not only the business user but also data warehouse administrators and developers. Without meta data‚ business users will be like tourists left

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    Primary Secondary Data

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    Secondary data is gathered via secondary research and involves information that has already been collated/interpreted by someone else for another purpose- for example: Census data Australian economic growth figures Tourist numbers Books‚ newspapers‚ magazines‚ internet articles on a certain subject There are two types of secondary data: Internal: data that has already been collected from internal sources such as internal sales data‚ consumer feedback and other research reports External: published

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