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    Big Data?

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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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    Data Modeling

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    Lecture Notes 1 Data Modeling ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova‚ MSIT 1 • Database: A collection of related data. • Data: Known facts that can be recorded and have an implicit meaning. – An integrated collection of more-or-less permanent data. • Mini-world: Some part of the real world about which data is stored in a database. For example‚ student grades and transcripts at a university. • Database Management System (DBMS): A software package/ system to facilitate

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    Big Data

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    V2 server for its SAP HANA database and S7700 and S5700 switches. Huawei’s SAP HANA application came about as a result of a successful switching project and helps Unicomm to analyse sales data in real time. “With the SAP HANA solution‚ we needed a partner that was ready to support us in every way possible. By helping us to stay in budget and to adopt a system that could grow in line with company requirements‚ Huawei really delivered.” Federico Vecchiatti‚ Head of IT‚ Unicomm “Before they started

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    Data Anomalies

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    Data Anomalies Normalization is the process of splitting relations into well-structured relations that allow users to inset‚ delete‚ and update tuples without introducing database inconsistencies. Without normalization many problems can occur when trying to load an integrated conceptual model into the DBMS. These problems arise from relations that are generated directly from user views are called anomalies. There are three types of anomalies: update‚ deletion and insertion anomalies. An update anomaly

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    Data mining

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    it for any other purpose. DATE: 06/10/2013 Introduction: In data mining it is said that “success or failure often depends not only on how well you are able to collect data but also on how well you are able to convert them into knowledge that will help you better manage your business (Wilson‚ 2001‚ p. 26).” Tourism and hospitality industry generates massive amount of data. In each and every transaction there is set of data generated. In tourism and hospitality‚ knowing your customer is very

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    Open-Data

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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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    Data Flow

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    DATA FLOW DIAGRAM - one of the most commonly used modeling tool which graphically represents a system as a network of processes‚ linked together through input and output flow lines and entities. Data flow Components ▪ Process - transformation of data flow into outgoing data flow. It may represent . . - whole system - subsystem - activity ▪ Data store - repository of data in the system It may represent . . . - computer file or

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    Data Analysis

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    Title: Data Analysis Word count: 1002 Contents: Introduction Procedure Findings Conclusion References Introduction: For my Data Analysis assignment I am required to present statistical data in an appropriate format. I will collect and analyse data using spread sheets‚ charts and graphs within a formal report. My report will present findings on how the internet has affected the UK economy and how is it transforming us as a nation? Procedure: I am going

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    DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm

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    2.2.3 Data Collection Another crucial stage that cannot be ignored is deciding on the type and nature of data that is to be used in the research. Ideally‚ there are three types of data that a researcher can collect using primary research. First‚ the data can be quantitative in nature. This refers to data that is capable of been converted into a numerical value (Kothari 2004). One of the benefits of quantitative data is that its measurement does not require critical reviews‚ making it easy to collect

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