You Can Do With Data/The Information Architecture of an Organization What is the difference between data and information? Give examples. Data = discrete‚ unorganized‚ raw facts Quantity Sold‚ Course Enrollment‚ Customer Name‚ Discount‚ Star Rating. Information = transformation of those facts into meaning. Financial data (deposits)‚ daily loans. What is a transaction? Action performed in a database management system What are the characteristics of an operational data store? Stores
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Master Thesis Electrical Engineering November 2011 Security Techniques for Protecting Data in Cloud Computing Venkata Sravan Kumar Maddineni Shivashanker Ragi School of Computing Blekinge Institute of Technology SE - 371 79 Karlskrona Sweden i This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering. The thesis is equivalent to 40 weeks of full time studies.
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Definition: Statistics is the study of the collection‚ organization‚ analysis‚ interpretation and presentation of data. It deals with all aspects of this‚ including the planning of data collection in terms of the design of surveys and experiments. A statistician is someone who is particularly well-versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained experience through working in any of a wide number of fields. Some
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Primary and Secondary Marketing Research When looking to add a new product to the market‚ traditionally five steps occur in marketing research and lead to marketing actions. Of these five steps‚ step number three covers the collection of marketing data. Marketing data can be collected through either primary research or secondary research. The goal of this assignment is to describe both primary and secondary research‚ provide examples of each and determine how the author’s organization could benefit
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types of communication between electrical devices. Distortion‚ noise‚ 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
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BCSCCS 303 R03 DATA STRUCTURES (Common for CSE‚ IT and ICT) L T P CREDITS 3 1 0 4 UNIT - I (15 Periods) Pseudo code & Recursion: Introduction – Pseudo code – ADT – ADT model‚ implementations; Recursion – Designing recursive algorithms – Examples – GCD‚ factorial‚ fibonnaci‚ Prefix to Postfix conversion‚ Tower of Hanoi; General linear lists – operations‚ implementation‚ algorithms UNIT - II (15 Periods)
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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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Lab – Data Analysis and Data Modeling in Visio Overview In this lab‚ we will learn to draw with Microsoft Visio the ERD’s we created in class. Learning Objectives Upon completion of this learning unit you should be able to: ▪ Understand the concept of data modeling ▪ Develop business rules ▪ Develop and apply good data naming conventions ▪ Construct simple data models using Entity Relationship Diagrams (ERDs) ▪ Develop entity relationships and define
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number of articles on “big data”. Examine the subject and discuss how it is relevant to companies like Tesco. Introduction to Big Data In 2012‚ the concept of ‘Big Data’ became widely debated issue as we now live in the information and Internet based era where everyday up to 2.5 Exabyte (=1 billion GB) of data were created‚ and the number is doubling every 40 months (Brynjolfsson & McAfee‚ 2012). According to a recent research from IBM (2012)‚ 90 percent of the data in the world has been
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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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