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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Table of Contents 1. VARIABLES- QUALITATIVE AND QUANTITATIVE......................3 1.1 Qualitative Data (Categorical Variables or Attributes) ........................... 3 1.2 Quantitative Data............................................................................................... 4 DESCRIPTIVE STATISTICS.................................................6 2.1 Sample Data versus Population Data ................................................................... 6 2.2 Parameters and Statistics
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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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Patrick Cunningham ITM220-J November 8‚ 2013 Big Data Big Data‚ an inspirational novel about the collection and processing of massive amounts of data was eye-opening and encouraging. This collection of data over a long period of time has been processed and used towards many different aspects throughout the world. Dilemmas such as tracking the H1N1 virus‚ to buying the most inexpensive plane tickets‚ all the way to predicting dangerous manholes explosions have all been processed and tabulated
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Data Collection QNT/351 July 10‚ 2014 There are many times when companies have to collect data to come to a conclusion about an issue. The data may be collected from their employers‚ their competition or their consumers. BIMS saw that there had been an average turnover that was larger then what the company had seen in the past. Human Resources decided that they would conduct a survey to see what had changed in the company from the employee’s point of view. They attached
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The scenario is the number of Wal-Mart stores for each year from 2003 - 2010. The data is (2003‚ 4906)‚ (2004‚ 5289)‚ (2005‚ 6141)‚ (2006‚ 6779)‚ (2007‚ 7262)‚ (2008‚ 7720)‚ (2009‚ 8416)‚ (2010‚ 8970). Each of these graphs is plotted with these points. With this plot I need to formulate a curve of best fit using the correlation coefficient. This graph is about the number of Walmart employees. The X-axis is the Time ( years after 2002). The Y-axis is the number of Walmart employees (in thousands)
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and cross talk on a cabling medium are factors that prevent the accuracy of transmitted data to be intact. For these reasons different encoding methods exist. An example is when 2 wires are used to transmit music data to a speaker Digital signals don’t always have to be carried over to the receiving end by electricity‚ light can also be used for digital communication. Fibre Optics use light to transmit data through optical fibre within the cable. The strength of the light ray can also be a determining
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DATA COMPRESSION The word data is in general used to mean the information in digital form on which computer programs operate‚ and compression means a process of removing redundancy in the data. By ’compressing data’‚ we actually mean deriving techniques or‚ more specifically‚ designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms‚ including both compression and decompression. Data Compression
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DATA COMMUNICATION (Basics of data communication‚ OSI layers.) K.K.DHUPAR SDE (NP-II) ALTTC ALTTC/NP/KKD/Data Communication 1 Data Communications History • 1838: Samuel Morse & Alfred Veil Invent Morse Code Telegraph System • 1876: Alexander Graham Bell invented Telephone • 1910:Howard Krum developed Start/Stop Synchronisation ALTTC/NP/KKD/Data Communication 2 History of Computing • 1930: Development of ASCII Transmission Code • 1945: Allied Governments develop the First Large Computer
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UNCLASSIFIED UNCLASSIFIED 1 Open Data Strategy June 2012 UNCLASSIFIED UNCLASSIFIED 2 Contents Summary ................................................................................................... 3 Introduction ................................................................................................ 5 Information Principles for the UK Public Sector ......................................... 6 Big Data .......................................................................
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