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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Research Project - Data Protection Data can be collected by organisations such as the websites we use daily‚ such as Facebook and Twitter. They have our information such as our age‚ date of birth‚ home address and other personal information which we would not share with strangers‚ and it is their job to protect that data‚ so that it doesn’t get into the wrong hands‚ such as scammers. Organisations may collect information from you in a number of ways‚ over the internet‚ over the phone‚ or also
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.......................................................................................... 3 2.1.2 Non-functional requirement ............................................................................................. 5 3. Logical design: Data Modeling (ERD) .................................................................................... 6 4. Logical design: Process Modeling (DFD) ............................................................................... 9 5. Decision
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Using Technology to Advance Learning Foundations of Online Learning American Military University USING TECHNOLOGY TO ADVANCE EDUCATION With the role of technology rapidly changing the world‚ we must change with it. During the 21st century our traditional approach to learning has changed forever. The traditional way of learning in a classroom setting has changed also. In the past‚ teachers have served as the primary source of information for students‚ but today teachers no longer lecture
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IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
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HATCO Data Set Description The HATCO data set gives data from a survey of customers of the HATCO company. The data set consists of 100 observations on 14 separate variables. Three types of information were collected. The first type of information is the perception of HATCO on seven attributes identified in past studies as the most influential in the choice of suppliers. The respondents‚ purchasing managers of firms buying from HATCO‚ rated HATCO on each attribute. Each of these 7 variables
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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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Programme Management Office Project Charter & Scope Statement Project Title: Project ID: Project Sponsor: Project Manager: Charter approval date: Project and Module Data Project Brian Norton‚ President Liam Duffy‚ IS Services Document Control Date 30-01-12 02-02-12 10-02-12 16-03-12 Version V 1.0 V 2.0 V 3.0 V 4.0 Changed by Liam Duffy Liam Duffy Liam Duffy Liam Duffy Reasons for Change Original Document Consultation with Sponsor Consultation with Project
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2 Areas of data processing 1. Business Data processing (BDP) . Business data processing is characterized by the need to establish‚ retain‚ and process files of data for producing useful information. Generally‚ it involves a large volume of input data‚ limited arithmetical operations‚ and a relatively large volume of output. For example‚ a large retail store must maintain a record for each customer who purchases on account‚ update the balance owned on each account‚ and a periodically present a
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and briefly describe each‚ and give your opinion about which shoplifting prevention and detection technique is the most effective and why. Shoplifting and detection are used in many stores to prevent theft. Below I will briefly discuss the six different ways they are used. Two-Way mirrors: These types of mirrors are used mostly in the retail trade such as department stores‚ supermarkets‚ and large variety and discount stores. The one watching the people can see through the mirror but the customer
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