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    Ethics, Big Data

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    student’s performance data and use it as a metric to measure a student’s ability to keep on a track that has worked for previous students. The universities collect the data from students from many years to help improve the learning experience of future students so that they may determine a students a current progress in a class and how it compares to others that have preceded them to allow the university to counsel the student if they are falling behind. In “Ethics‚ Big Data‚ and Analytics: A Model

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    big data by oracle

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    Financial Services Data Management: Big Data Technology in Financial Services Big Data Technology in Financial Services Introduction: Big Data in Financial Services ....................................... 1 What is Driving Big Data Technology Adoption in Financial Services?3 Customer Insight ........................................................................... 3 Regulatory Environment ................................................................ 3 Explosive Data Growth ........

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    CHAPTER 2 DATA COLLECTION AND PRESENTATION 2.1 Data Collection This section aims to: 1. Identify‚ compare and contrast the different types of data; 2. List and explain the various techniques of selecting a sample; and 3. Enumerate and illustrate the different sampling techniques Types of Data Data is a collection of facts‚ such as values or measurements. It can be numbers‚ words‚ measurements‚ observations or even just descriptions of things. Two types of Data Primary Data means original

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    Data Protection Act

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    to confidentiality. They are: • Data protection act 1998 • Access to personal files act 1987 • Access to medical records act 1990 The following have to follow legislation mentioned above: • Nurseries-private/government based/child minders/nannies • Hospitals-private/government funded • Schools-private/government funded • Doctor surgeries • Care homes • NHS Data protection act 1998 The Data protection act was developed to give

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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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    Data Analysis Grid

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    Data Collection and Analysis Grid * Use the two articles assigned by your facilitator to identify the following data collection‚ analysis‚ and measurement elements for the studies. Limit each box to no more than three sentences. * * | * Qualitative | * Quantitative | * Data collection methods | * This qualitative study used a focus group interview as the main data collection method with a semi-structured design. | * The study employed an experimental pre-test/post-test

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    Data Warehousing Failures

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    Data Warehousing Failures Eight studies of data warehousing failures are presented. They were written based on interviews with people who were associated with the projects. The extent of the failure varies with the organization‚ but in all cases‚ the project was at least a disappointment. Read the cases and prepare a one or two page discussion of the following: 1. What’s the scope of what can be considered a data warehousing failure? Discuss. 2. What generalizations apply across

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    Data Collection Methods

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    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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    Data Mining Fundamentals

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    Data Mining DM Defined Is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner Process of analyzing data from different perspectives and summarizing it into useful information A class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. DM Defined The relationships and summaries derived

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    Data Envelopment Analysis

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    Chapter 12 Data Envelopment Analysis Data Envelopment Analysis DEA is an increasingly popular management tool. This write-up is an introduction to Data Envelopment Analysis DEA for people unfamiliar with the technique. For a more in-depth discussion of DEA‚ the interested reader is referred to Seiford and Thrall 1990 or the seminal work by Charnes‚ Cooper‚ and Rhodes 1978 . DEA is commonly used to evaluate the e ciency of a number of producers. A typical statistical approach is characterized

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