Big Data‚ Data Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse
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Mohammed Al Bittar - 1006091 1. What is meant by big data? A term used for complex sets of data which becomes very difficult to process‚ manage‚ or capture by commonly-used software. 2. What is meaning of data-driven culture? A culture where decisions made upon analyzing real statistical information. Like how Wal-Mart checks on the weather in order to provide more products to the customers; because their statistical information shows that whenever there is a storm‚ customers by
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Risk and Return: Portfolio Theory and Asset Pricing Models Portfolio Theory Capital Asset Pricing Model (CAPM) Efficient frontier Capital Market Line (CML) Security Market Line (SML) Beta calculation Arbitrage pricing theory Fama-French 3-factor model Portfolio Theory • Suppose Asset A has an expected return of 10 percent and a standard deviation of 20 percent. Asset B has an expected return of 16 percent and a standard deviation of 40 percent. If the correlation between A and B is 0.6
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Data Mining Weekly Assignment 6: LIFT; CRM; AFFINITY POSITIONING; CROSS-SELLING AND ITS ETHICAL CONCERNS. What is meant by the term “lift”? The term “lift” describes the improved performance of an exact or specific amount of effort on a modeled sampling‚ as opposed to a random sampling (Spang‚ 2010). In other words‚ if you are able to market via a model to say‚ a given number of random customers (e.g. 1000)‚ and we expect that 50 of them would be successful‚ then a model that can generate 75
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.......................................................................................... 3 2.1.2 Non-functional requirement ............................................................................................. 5 3. Logical design: Data Modeling (ERD) .................................................................................... 6 4. Logical design: Process Modeling (DFD) ............................................................................... 9 5. Decision
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THE STRATEGY EXECUTION SOURCE Article Reprint No. B0911A Risk Management and the Strategy Execution System By Robert S. Kaplan For a complete list of Harvard Business Publishing newsletters: http://newsletters.harvardbusiness.org For reprint and subscription information for Balanced Scorecard Report : Call 800-988-0866 or 617-783-7500 http://bsr.harvardbusinessonline.org For customized and quantity orders of reprints: Call 617-783-7626 Fax 617-783-7658 For permission
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Identify and briefly explain three reasons why the New Christian Right might have failed to achieve its aims (9marks) The New Christian Right is a politically and morally conservative‚ protestant fundamentalist movement. The aims are extremely ambitious as they wish to make abortion‚ homosexuality and divorce illegal. They want to turn back to a time before liberalisation of American culture and society began. The New Christian Right may have failed to achieve its aims because the group lacked wide
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Data Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus‚ data mining should have been more appropriately named “knowledge mining from data‚” which is unfortunately somewhat long. Knowledge mining‚ a shorter term‚ may not
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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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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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