Uniform Hospital Discharge Data Set Veronica Burgos Kaplan University The year was 1969‚ when a conference was held by the National Center for Health Services Research and Development and Johns Hopkins to address hospital discharge abstract systems. A hospital discharge abstract system is an “abstraction of minimum data set from hospital charts for the purpose of producing summary statistics about hospitalized patients” (Porta‚ 2014). During that conference participants discussed the possibility
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Introduction to Data Modeling and MSAccess CONTENT 1 2 3 4 5 6 Introduction to Data Modeling ............................................................................................................... 5 1.1 Data Modeling Overview ............................................................................................................... 5 1.1.1 Methodology .......................................................................................................................... 6 1.1.2 Data Modeling
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DATA | INFORMATION | 123424331911 | Your winning lottery ticket number | 140593 | Your date of birth | Aaabbbccd | The grades you want in your GCSEs | Data and information Data‚ information & knowledge Data Data consist of raw facts and figures - it does not have any meaning until it is processed and turned into something useful. It comes in many forms‚ the main ones being letters‚ numbers‚ images‚ symbols and sound. It is essential that data is available because it is the first
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of constraints. Ans: A Q.2 Relational calculus is a (A) Procedural language. (C) Data definition language. Ans: B Q.3 The view of total database content is (A) Conceptual view. (C) External view. Ans: A Q.4 Cartesian product in relational algebra is (A) a Unary operator. (B) a Binary operator. (C) a Ternary operator. (D) not defined. Ans: B Cartesian product in relational algebra is a binary operator. (It requires two operands. e.g.‚ P X Q) Q.5 DML is provided for (A) Description of logical structure
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Systems Coursework Part 1: Big Data Student ID: 080010830 March 16‚ 2012 Word Count: 3887 Abstract Big data is one of the most vibrant topics among multiple industries‚ thus in this paper we have covered examples as well as current research that is being conducted in the field. This was done based on real applications that have to deal with big data on a daily basis together with a clear focus on their achievements and challenges. The results are very convincing that big data is a critical subject that
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Data Projectors Amy Shipman $50- $66‚525 What is a data projector? It is “a device that projects computer output onto a white or silver fabric screen that is wall‚ ceiling or tripod mounted." The three most common types of data projectors are the LCD‚ DLP‚ and the LCoS. Each type of projector will project your audio and video‚ they just have different ways to process the output of your audio and video. DLP stands for Digital Light Processing. This type of data projector has a light that
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SMS CUSAT Reading Material on Data Mining Anas AP & Alex Titty John • What is Data? Data is a collection of facts and information or unprocessed information. Example: Student names‚ Addresses‚ Phone Numbers etc. • What is a Database? A structured set of data held in a computer which is accessible in various ways. Example: Electronic Address Book‚ Phone Book. • What is a Data Warehouse? The electronic storage of large amount of data by business. Concept originated in
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Interpreting your data is a process that involves answering a series of questions about the research. We suggest the following steps: 1) Review and interpret the data "in-house" to develop preliminary findings‚ conclusions‚ and recommendations. 2) Review the data and your interpretation of it with an advisory group or technical committee. This group should involve local‚ regional‚ and state resource people who are familiar with monitoring and with your product. They can verify‚ add to‚ or
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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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University CS 450 Data Mining‚ Fall 2014 Take-Home Test N#1 Date: September 22nd‚ 2014 Final deadline for submission September 29th‚ 2014 Weighting: 5% Total number of points: 100 Instructions: 1. Attempt all questions. 2. This is an individual test. No collaboration is permitted for assessment items. All submitted materials must be a result of your own work. Part I Question 1 [20 points] Discuss whether or not each of the following activities is a data mining task.
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