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

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    Data Security in Healthcare Data Security in Healthcare In the world of technology today‚ consumers often purchase items through the internet using their personal information such as name‚ date of birth and credit card numbers. This information can easily be stolen from someone who seeks to exploit weakness in a computer network. According‚ to (Gagne‚ 2012)‚ “data breaches often occur through technical vulnerabilities‚ malware‚ compromised user credentials or opportunist attackers”

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    Health Data Exchange

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    Effectiveness of Health Data Exchange Introduction: The major goal for moving towards the electronic health care exchange is to have improvement in the health care and also have the lowering of costs. The health care is seen to be one of the largest segments which account for 20% of the US GDP. Research has shown that Health Information Exchanges (HIEs) has provided the HITECH (Health Information Technology for Economic and Clinical Health) which gas made more than $15.5 billion available to the

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    A MULTIDIMENSIONAL DATA MODEL Data warehouses and OLAP tools are based on a multidimensional data model. This model views data in the form of a data cube. FROM TABLES TO DATA CUBES What is a data cube? A data cube allows data to be modeled and viewed in multiple dimensions. It is defined by dimensions and facts. In general terms‚ dimensions are the perspectives or entities with respect to which an organization wants to keep records. Each dimension may have a table associated with it‚ called

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    Finding the right data

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    When looking for data‚ it is important that school administration and teachers know what to look for. They can define their search by formulating essential questions with which to answer using the data. The essential questions will lead to goals that the school strives towards by researching the data. Data may include online databases‚ site based databases‚ spreadsheets‚ test scores and various other collection sources. The data can be collected on various online and printed forms used for documentation

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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 Depth and Optimization Komei Fukuda fukuda@ifor.math.ethz.ch Vera Rosta rosta@renyi.hu In this short article‚ we consider the notion of data depth which generalizes the median to higher dimensions. Our main objective is to present a snapshot of the data depth‚ several closely related notions‚ associated optimization problems and algorithms. In particular‚ we briefly touch on our recent approaches to compute the data depth using linear and integer optimization programming. Although

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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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    Gene Expression Data

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    Microarray Technology | 7 | | 1.2.1 Measuring mRNA levels | 7 | | 1.2.2 Pre-processing of Gene Expression Data | 8 | | 1.2.3 Applications of Clustering Gene Expression Data | 9 | | 1.3 Mutual Information | 10 | | 1.4 Introduction to Clustering Techniques | 11 | | 1.4.1 Clusters and Clustering | 11 | | 1.4.2 Categories of Gene Expression Data Clustering | 11 | | 1.5 Semi-supervised Learning | 12 | | 1.5.1 Semi-supervised Classification |

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    Target Data Breach

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    TARGET DATA BREACH 2013/14 Introduction There are many types of breaches that can occur when it comes to secure systems and networks. The target breach of 2013/14 was due to human error. It is said that the company had easily stolen credentials. If there was the necessary secure measures taken‚ this breach could have been stopped. Target did not have an adequate firewall which is why the hackers were able to corrupt the system and steal personal information and credit card information. This whole

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    Data Report and Analysis

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    Data Report and AnalysisBritnee Burleson Tyler Junior CollegeAbstract This report attempts to determine my personality type by analyzing the Type Focus assessment results in order to find out my personality type and if it is compatible with my career choice. Research generated four letter personality type‚ three main interest‚ and three work values. These results will be discussed in Method‚ Results‚ and Discussion. Data Report and AnalysisIntroduction: Starting anew at Tyler Junior College was

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