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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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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feed in and other 12% balance is water‚ the scaling factor that is used is 162.004389. Based on the overall mass balance in table 6.4‚ it shows that this process is not balance but yet has low percentage of error which is 1.8%. Mass balance of the production of acetone can be considered as acceptable due to the low error
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11 2.2 Global Scenario 11 2.3 Indian Scenario: 17 3 Performance Review of X Plan Period 25 3.1 Introduction 25 3.2 Hydrocarbon Reserve Position 25 3.3 Crude Oil and Natural Gas Production 26 3.4 Implementation of New Exploration Licensing Policy (NELP) 28 3.5 Implementation of Coal Bed Methane (CBM) Policy 28 3.6 Equity Oil and Gas from Abroad 29 3.7 Consumption of Petroleum Products during X Plan 31 3.8 Refining Capacity 32 3.9 Investments 33 4 Review of Policy Measures 36 4.1 Marketing
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recognition system. GMM parameters are estimated from training data using the iterative Expectation-Maximization (EM) algorithm or Maximum A Posteriori (MAP) estimation from a well-trained prior model. Main Body Text Introduction A Gaussian mixture model is a weighted sum of M component Gaussian densities as given by the equation‚ M wi g(x|µi ‚ Σi )‚ p(x|λ) = (1) i=1 where x is a D-dimensional continuous-valued data vector (i.e. measurement or features)‚ wi ‚ i = 1‚ . . . ‚ M
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ECONOMICS FOR BUSINESS Project Report on – Oil and the recent ‟Dutch Disease‟ - The Case of the United Arab Emirates Submitted by – Amitava Manna 1|Page Table of Contents Introduction .................................................................................................................................................. 2 Purpose ....................................................................................................................................................
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Data Warehousing‚ Data Marts and Data Mining Data Marts A data mart is a subset of an organizational data store‚ usually oriented to a specific purpose or major data subject‚ that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization. Data marts are often derived from subsets of data in a data warehouse‚ though in the bottom-up data warehouse design methodology the data
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PRODUCTION PLANNING TERM PROJECT | | | Course Lecturer: Prof.Dr.Selim Zaim Öğr.Gör.Dr.Hüseyin Selçuk Kılıç | | | | | Project Members: Elif Duygu Bağatırlar 150308045 Merve Ağaoğlu 150308026 İbrahim Ahıskalı 150308006 QUESTION 1 * Moving Average Method | | MA(2) | MA(3) | MA(4) | MA(5) | MA(6) | MA(2) | MA(3) | MA(4) | MA(5) | Month | Demand | one-step ahead | one-step ahead | one-step ahead | one-step ahead | one-step ahead | two
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Be Data Literate – Know What to Know by Peter F. Drucker Executives have become computer literate. The younger ones‚ especially‚ know more about the way the computer works than they know about the mechanics of the automobile or the telephone. But not many executives are information-literate. They know how to get data. But most still have to learn how to use data. Few executives yet know how to ask: What information do I need to do my job? When do I need it? In what
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Data Gathering ➢ used to discover business information details to define the information structure ➢ helps to establish the priorities of the information needs ➢ further leads to opportunities to highlight key issues which may cross functional boundaries or may touch on policies or the organization itself ➢ highlighting systems or enhancements that can quickly satisfy cross-functional information needs ➢ a complicated task especially in a large and complex system ➢ must
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