...When hearing the word schema people would not be able to explain what it means, and not realize that they use it in their everyday life. However it’s simple, schema is a concept that helps organize and interpret information. Schemas can be useful, because they allow us to take shortcuts in understanding a large amount of information. However, the concept can also cause us to reject relevant information in favor of information that confirms our pre-existing beliefs and ideas. Schemas can contribute to stereotypes and make it difficult to recall new information. So in order to understand schemas and the effects it has on a person’s life I formed a small case study. To start with, when starting the project, I first asked 10 participants who are in my family as well as my friends to help me in a project for psychology. Secondly I told the participants “I’m going to recite 12 words to you and show you those words at the same time.” The words were: Rest, Tired, Awake, Dream, Snore, Bed, Eat, Slumber, Sound, Comfort, Wake, and Night. After reciting the words I asked each participants what their name, age, and occupation was and when I went back to the list of words it seemed as all the words I recited to them didn’t matter, since they were more focused on the series of questions I asked 30 seconds after reciting the words. Next, I had asked the participants to write all the words they could remember within two minutes, but almost all ten participants had given up within a minute, since...
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...SCHEMATA A schema (pl. schemata or schemas), is a mental structure that represents some aspect of the world. People use schemata to organize current knowledge and provide a framework for future understanding. Schemata influence our attention, as we are more likely to notice things that fit into our schema. If something contradicts our schema, it may be encoded or interpreted as an exception or as unique. Thus, schemata are prone to distortion. They influence what we look for in a situation. They have a tendency to remain unchanged, even in the face of contradictory information. We are inclined to place people who do not fit our schema in a "special" or "different" category, rather than to consider the possibility that our schema may be faulty. As a result of schemata, we might act in such a way that actually causes our expectations to come true. Schemata can influence and hamper the uptake of new information (proactive interference), such as when existing stereotypes, giving rise to limited or biased discourses and expectations (prejudices), may lead an individual to "see" or "remember" something that has not happened because it is more believable in terms of his/her schema. For example, if a well-dressed businessman draws a knife on a vagrant, the schemata of onlookers may (and often do) lead them to "remember" the vagrant pulling the knife. Such distortion of memory has been demonstrated. A schema for oneself is called a "self schema". Schemata for other people are called...
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...Functional Guide Exigen Suite Release: 3.6 Dynamic Analytics Dashboard Administrator's Guide Document number: Platform_DynamicAnalyticsDasboard_FG_3.6 Revised: 10-11-2011 EXIGEN CONFIDENTIAL – FOR AUTHORIZED USERS ONLY Important Notice Information in this document, as well as the software products and programs described in it, is furnished by EIS Properties, Ltd. and/or affiliates (Exigen Insurance Solutions, Inc.) under license and may be used or copied only in accordance with the terms of such license. This document, the information contained in it, as well as the software products and programs desc ribed herein are considered confidential, proprietary, trade secrets of Exigen Insurance Solutions, Inc.). You may not copy, create derivatives, decipher, decompile, develop, or otherwise reverse engineer this document, the information contained in it, or the software products and programs described. Exigen Insurance Solutions, Inc. and its licensors retain all intellectual property and ownership rights to the information contained herein, as well as the software products and programs (including, but not limited to, software libraries, interfaces, source codes, documentation and training materials) described herein. The content of this document is furnished for informational use only, is subject to change without notice, may contain techni cal inaccuracies or typographical errors, and should not be construed as a representation, warranty or commitment by Exigen ...
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...OpenTravel™ Alliance XML Schema Design Best Practices Version 3.04 June 2006 © 2005 OpenTravel™ Alliance www.opentravel.org/ OpenTravel™ Alliance Best Practices Specification Page 2 1 2 3 OTA XML Schema Design Best Practices............................................................................. 4 XML Standard Specifications................................................................................................. 5 Best Practices.......................................................................................................................... 6 3.1 Scope.............................................................................................................................. 6 3.2 Schema Design Component Parts and Roles ................................................................. 6 4 OTA XML Schema Design Guidelines .................................................................................. 7 4.1 Tag Naming Conventions .............................................................................................. 7 4.1.1 Mixed Case ................................................................................................................ 7 4.1.2 Underscore................................................................................................................. 7 4.1.3 Acronyms................................................................................................................... 7 4.1.4 Word Abbreviations...
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...CIV E 603: Information Modeling and Database Systems Lecture 1 1 What to Study? Introduction to Data base Relational Model Database design Structured Query Language (SQL) 22 Let’s begin the journey !! …. in to fascinating world of databases 23 Today’s outline Database Management System (DBMS) Entity-Relationship (ER) Model 24 What is a database? Many people would like to call it organization… 25 What is a database? Database is a structured collection of related data. Many name it efficiency… 26 A database is A home for data – since that is where data stay… A manager for data – since data are organized neatly… A GOOGLE for data – since a particular record can be found in a snap… A guardian for data – since a database rejects malicious accesses… … 27 What is a Database? Database: is a collection of related data Data: known facts that can be recorded and that have implicit meaning Properties of database: • represents some aspect of the real world (mini-world -UoD) • logically coherent collection of data with some inherent meaning. A random assortment of data cannot correctly be referred to as a database. • designed, built, and populated with data for a specific purpose. It has an intended groups of users. 28 What is a Database? A database can be of any size and of varying complexity. • For example, the list of...
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...Personal Reflection on the Self There are key questions in which social psychology is based upon. First, what is the self? Next why do human beings develop a self?, and is it different from other people. Also, why is a person so over concerned or worried about “oneself”? Even though these are only a few questions, the answers maintain what make social psychology what it is. The reason that self is not a fixed object that exist, but rather, a term that varies from person to person is what the study of social psychology explains. If you were to do a survey and question people in two different locations about there interpretation of self, you would get several different answers. Yes there may be multiple answers, however, it does not mean that any of the answers are incorrect. As a matter of fact, each person will come up with their own self based of their own train of thought. This concept leads to another inquiry, which is of “how many self's” exist. Automatically, your instinct confirms that there is more than one; considering we all view the interpersonal self, body self, the societal self, and inner self. The way that others see you doesn't necessarily mean this is the way you may consider yourself in the same way, this is what can be referred to as self-recognized self identity. There are several terms that follow this theory. One example would be the spotlight effect. This is the state of mind that places ones mind at the center of the universe. This cause people to...
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...Practices Know Where to Go for More Information QlikView is not SQL (SQL Schemas) SQL take a large schema and queries a subset of tables. Each query creates a temporary “Schema” of only a few tables. Query result sets are independent of each other. Query 1 Query 2 QlikView is not SQL (QV Schemas) QlikView builds a smaller and more reporting friendly schema from the transactional database. This schema is persistent and reacts as a whole to user “queries”. A selection affects the entire schema. QlikView is not SQL (Aggregation and Granularity) Store Table Store A B SqrFootage 1000 800 Sales Table Store A A A B B Prod 1 2 3 1 2 Price $1.25 $0.75 $2.50 $1.25 $0.75 Date 1/1/2006 1/2/2006 1/3/2006 1/4/2006 1/5/2006 Select * From Store, Sales Where Store.Store = Sales.Store will return: SqrFootage 1000 1000 1000 800 800 Store A A A B B Prod 1 2 3 1 2 Price $1.25 $0.75 $2.50 $1.25 $0.75 Date 1/1/2006 1/1/2006 1/1/2006 1/1/2006 1/1/2006 Sum(SqrFootage) will return: 4600 If you want the accurate Sum of SqrFootage in SQL you can not join on the Sales table in the same Query! QlikView is not SQL (Benefits) • QlikView allows you to see the results of a selection across the entire schema not just a limited subset of tables. QlikView is not SQL (Benefits) • QlikView allows you to see the results of a selection across the entire schema not just a limited subset of tables. QlikView will aggregate at the lowest level...
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...Dealing with Missing Information in a Data Warehouse Today businesses are investing many resources in building data warehouses and data marts to obtain timely and actionable information that will give them better business insight. This will enable them to achieve, among other things, sustainable competitive advantage, increased revenues and a better bottom line. In the early '90s, data warehousing applications were either strategic or tactical in nature. Trending and detecting patterns was the typical focus of many solutions. Now, companies are implementing data warehouses or operational data stores which meet both strategic and operational needs. The business need for these solutions usually comes from the desire to make near real-time actions in a constantly changing environment while receiving information from both internal as well as external source systems. Dealing with missing or unknown data is critical in these types of environments. Unknowns skew metrics and results to produce incorrect decisions. Knowledge of the unknown allows at least for further examination of any conclusions drawn from incomplete data. Furthermore, in a well-designed business intelligence environment, these unknowns are often resolved later as data that is more complete is entered into the operational systems. Irrespective of the nature of the applications, missing information has always been a problem for data warehouses. As business intelligence environments become more mature, real time and...
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...RYERSON UNIVERSITY Ted Rogers School of Information Technology Management And G. Raymond Chang School of Continuing Education COURSE OF STUDY 2013-2014 (C)ITM 500 – Data and Information Management 1.0 PREREQUISITE The prerequisite for this course is [(C)ITM100 and (C)ITM207] or (C)ITM 305. Students who do not have the prerequisite will be dropped from the course. 2.0 INSTRUCTOR INFORMATION • • • • • Name: Office Phone Number: E-mail address: Faculty/course web site(s): https://my.ryerson.ca Office Location & Consultation hours: • Your instructor is available for personal consultation during scheduled consultation hours which are posted on their office door or on the course Blackboard site. However, you are advised to make an appointment by e-mail or by telephone before coming to ensure that the professor is not unavoidably absent. • E-mail Usage & Limits: Students are expected to monitor and retrieve messages and information issued to them by the University via Ryerson online systems on a frequent and consistent basis. Ryerson requires that any official or formal electronic communications from students be sent from their official Ryerson Email account. As such emails from other addresses may not be responded to. 3.0 CALENDAR COURSE DESCRIPTION This course provides the students with an introduction to the core concepts in data and information management. It is centered around conceptual data modeling techniques, converting the conceptual data models into relational...
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...The Importance of Data Warehousing Brenda L Bach The Digital Firm and Business Communications/BU 204-8A November 15, 2014 Ron Rosalik Kenneth and Jane Laudon state that a data warehouse is a database that stores current and historical data that can be of potential interest to decision makers throughout the corporation (Laudon, 2011. p.225). They go on to explain that the data can originate from many core operational transaction systems and could include data from Web site transactions (Laudon, 2011 p.225). Data warehouse extract current along with historical data from all operational systems within an organization. The data warehouse makes the data it collects and stores available to anyone and can be accessed and viewed as needed but cannot be altered in any manner. These data warehouses also provide a large range of ad hoc as well as analytical tools and graphical reports that represent the data. Companies often build enterprise data warehouses and either uses a central data warehouse or a smaller decentralized warehouse called a data mart to preserve the data they collect through its many sources. A data mart is a subset of a data warehouse that summarizes on a highly focused portion of the organization’s data and is placed within a separate data based for a very specific population of users. For example, a car dealer that deals with car sales as well as service may use a data mart to develop marketing and sales data that are specifically focused on the data of the...
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...The Self Paper Maggie Morrison PSYCH/555 November 11, 2013 Deirdre Teaford The concept of self The concept of self is an assortment of belief and understanding of how each person see things differently because of their feelings, beliefs, interpersonal relationship, and attitude. The term self identifies a person racial, sexual and gender roles, it is what makes them different from everyone else. In order to determine a successful investigate, social psychologist have separated self concept in two structures: conceptual and operational. Conceptual is define as self-concept which is separated into four characteristics, that consist of the material self, the inner self, the interpersonal self and the societal self, which is a reflection of a person and their different roles interactions with others. A person’s personality, characteristics, appearances, and social qualities is what makes you, it creates a difficult person of knowing and understanding the real you is not so easy. Finally, this image was created in many ways; however, it is influenced by our interactions with significant people in our lives (Cherry, 2013). Each person self consists of characteristic and personality traits distinguish us from other people. The relational of self is having personal relationships with your husband, wife, mother, father, sister, and brother. Self-concept represents the person I am or the person I have become. Self-concept is also made up as one self schema, which works together...
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...Section A: One to Many (1:M) Relationship 1. Base on the following description; draw a conceptual data model using the entity relationship diagramming technique. a) Employee Number identifies an employee. Employee name is kept. b) Each customer has a unique customer number. His name, address are recoded. c) An employee is assigned to attend to one or more customers. Not all employees attend customers. d) A customer must be attended to by only one employee. Section B: Cardinality (outer symbols) Constraints of a Relationship 2. In question 1, what is the cardinality of the relationship “attend”? a) one to one b) one to many c) many to many d) One to zero…………………………………………………( ) Section C: Participation (inner symbols) Constraints of a Relationship 3. In question 1, which sub-point refers to mandatory participation and which sub-point refers to optional participation? Section D: Many to Many (M:N) Relationship With Attributes 4. Based on the following description, draw a conceptual data model using the entity relationship diagramming technique. i. A customer may order many products. ii. A product may be ordered by many customers. iii. A customer has a unique customer number, name and email. iv. A product has a unique product code, description and unit price. v. The date ordered and the quantity ordered by the customer for...
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...An Analysis of XML Database Solutions for the Management Of MPEG-7 Media Descriptions MOHSIN ARSALAN SZABIST KARACHI, PAKISTAN Abstract: MPEG-7 based applications will be set up in the near future due to its promising standard for the description of multimedia contents. Therefore management of large amount of mpeg-7 complaint media description is what is needed. Mpeg documents are XML documents with media description schemes defined in xml schema. In this paper are mentioned some of the solutions that help make a management system for mpeg-7. Furthermore these solutions are compared and analyzed. The result shows how limited today’s databases are, when comes the case of mpeg-7. Keywords: MPEG-7, XML, SCHEMA 1. INTRODUCTION The paper is organized in the following manner that sec1 is the introduction to what mpeg-7 is. Then the solutions for its management are mentioned. Then the solutions are analyzed and finally in the end the conclusion is mentioned. 1.1. MPEG-7: Mpeg (moving picture expert group) is the creator of the well known mpeg1 and mpeg2 and mpeg4. Mpeg-7 is an ISO standard which is developed by mpeg group. The mpeg-7 standard formally named “multimedia content description interface” provides a rich of standardized tools which describes a multimedia content. Humans as well as automatic systems process audiovisual information which is within the mpeg7 scope. Audiovisual description tools (the metadata elements and their structure and relationships...
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...About Cognizant Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting and business Process outsourcing services. Cognizant’s single-minded passion is to dedicate our global technology and Innovation know-how, our industry expertise and worldwide resources to working together with clients to make their business stronger. With more than 40 global delivery centers and approximately 61,700 employees as of December 31, 2008, we combine onsite/offshore model infused by a distinct culture of customer satisfaction. A member of the NASDAQ-100 Index and S&P 500 Index, Cognizant is a Forbes Global 2000 company and a member of the Fortune 1000 and is ranked among the top information technology companies in Business Week’s Hot Growth and Top 50 Performers listings Start Today For more information on how to drive your business results with Cognizant, contact us at inquiry@cognizant.com or visit our website at: www.cognizant.com. World Headquarters 500 Frank W. Burr Blvd. Teaneck, NJ 07666 USA Phone: +1 201 801 0233 Fax: +1 201 801 0243 Toll Free: +1 888 937 3277 Email: inquiry@cognizant.com European Headquarters Haymarket House 28-29 Haymarket London SW1Y 4SP UK Phone: +44 (0) 20 7321 4888 Fax: +44 (0) 20 7321 4890 Email: infouk@cognizant.com India Operations Headquarters #5/535, Old Mahabalipuram Road Okkiyam Pettai, Thoraipakkam Chennai, 600 096 India Phone: +91 (0) 44 4209 6000 Fax: +91 (0) 44 4209 6060 Email: inquiryindia@cognizant.com ...
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...Data Warehouse Design: Dimensional Modeling II Data Technology Chularat Tanprasert, Ph.D. Recap Dimensional modeling Popular, useful, and pragmatic approach Based on Kimball Fact table Dimension tables Design process in steps Database Schema Design Star Schema (With Attributes) Example Designs A useful way to learn about data warehouse design principles is by using examples – reuse. Kimball – Data warehouse lifecycle toolkit Adamson & Venerable – Data warehouse design solutions Let’s take a look at inventory, shipments, and financial services. Inventory An inventory system serves as a “middleman” between the manufacturer and the retailer – value adding process. There are threee types of inventory model Inventory snapshot Delivery status Transaction Inventory Snapshot Model For specific time periods, inventory levels are measured and recorded. Delivery Status Model Create one record for each complete shipment of a product to a warehouse. Transaction Model Record every transaction that affects the inventory. Shipments The shipments process is where the product leaves a company and is delivered to a customer. Typically, accompanying each shipment is a shipment invoice. Each line item on the shipment invoice corresponds to an SKU. Shipments Shipments Shipments Financial Services Typically a large bank. Services...
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