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    Data Gathering

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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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    data mining

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    Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific

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    Data Center

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    Increase Your Data Center Energy Efficiency • Increase Your Data Center Energy Efficiency • Increase Your Data Center Energy Efficiency • Increase Your Data Center Energy Efficiency • Increase Key Best Practices Optimize the Central Plant Quick Start Guide to Increase Data Center Energy How To Start A Problem That You Can Fix Data Center energy efficiency is derived from addressing BOTH your hardware equipment AND your infrastructure. Commit to Improved Design and Operations

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    Big Data

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    Turning data into information © Copyright IBM Corporation 2007 Course materials may not be reproduced in whole or in part without the prior written permission of IBM. 4.0.3 Unit objectives After completing this unit‚ you should be able to: Explain how Business and Data is correlated Discuss the concept of turning data into information Describe the relationships between DW‚ BI‚ and Data Insight Identify the components of a DW architecture Summarize the Insight requirements and goals of

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    Data Mining

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    indexes were selected (static and dynamic complexity index) and a Business Dynamic model was developed. This model was used with empirical data collected in a job shop manufacturing system in order to test the usefulness and validity of the dynamic complex index. The Business Dynamic model analyzed the trend of the index in function of different inputs in a selected work center. The results showed that the maximum value of the dynamic complexity index represents the so called “edge of chaos”‚ where the

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    Analysis of Data

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    Analysis of Data The researcher distributed 150 questionnaires to people and students from different schools. After collecting the papers‚ each was tallied one by one. The questionnaire has a total of Seven(7) questions each with a different set and amount of answers. One hundred(100) questionnaires were distributed in person while the Fifty(50) were answered online. The results of the survey will be explained by percentage and shown through pie chart as well along with a slight conclusion for

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    Big Data

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    Case Study Italian retailer Unicomm selects Huawei RH5885 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

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    Data Communications

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    Introduction Data communications (Datacom) is the engineering discipline concerned with communication between the computers. It is defined as a subset of telecommunication involving the transmission of data to and from computers and components of computer systems. More specifically data communication is transmitted via mediums such as wires‚ coaxial cables‚ fiber optics‚ or radiated electromagnetic waves such as broadcast radio‚ infrared light‚ microwaves‚ and satellites. Data Communications =

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    Data Mining

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    Data Mining And Statistical Approaches In Identifying Contrasting Trends In Reactome And Biocarta By Sumayya Iqbal SP09-BSB-036 Zainab Khan SP09-BSB-045 BS Thesis (Feb 2009-Jan 2013) COMSATS Institute of Information Technology Islamabad- Pakistan January‚ 2013 COMSATS Institute of Information Technology Data Mining And Statistical Approaches In Identifying Contrasting Trends In Reactome And Biocarta A Thesis Presented to COMSATS Institute of Information Technology‚ Islamabad In

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    Choosing a major

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    Choosing a College Major Based on Your Personality What does the research say? Information and advice for students and adults returning to school‚ as well as parents‚ counselors‚ faculty advisors‚ and education policymakers. Lawrence K. Jones‚ Ph.D.‚ NCC © 2010 - 2013 by Career Key‚ Inc. www.careerkey.org Copyright holder is licensing this under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. You are free to copy‚ share‚ post on your blog‚ or email for non-commercial

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