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    Data Replication

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    Outline  Introduction  Distributed DBMS Architecture  Distributed Database Design  Distributed Query Processing  Distributed Transaction Management  Data Replication  Consistency criteria  Update propagation protocols  Parallel Database Systems  Data Integration Systems  Web Search/Querying  Peer-to-Peer Data Management  Data Stream Management Distributed & Parallel DBMS M. Tamer Özsu Page 6.1 Acknowledgements  Many of these slides are from notes prepared by  Prof. Gustavo

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    Data Collection

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    Data collection is any process of preparing and collecting data‚ for example‚ as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record‚ to make decisions about important issues‚ or to pass information on to others. Data are primarily collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project‚ and is often formalized through a data collection plan which often

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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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    Data Mining

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    Data Mining: What is Data Mining? Overview Generally‚ data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue‚ cuts costs‚ or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles‚ categorize it‚ and summarize the relationships identified

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    Data Modeling

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    Lecture Notes 1 Data Modeling ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova‚ MSIT 1 • Database: A collection of related data. • Data: Known facts that can be recorded and have an implicit meaning. – An integrated collection of more-or-less permanent data. • Mini-world: Some part of the real world about which data is stored in a database. For example‚ student grades and transcripts at a university. • Database Management System (DBMS): A software package/ system to facilitate

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    Hair Transplant Recovery Timeline Hair transplant surgery is moderately complicated and takes about 4 hours to complete. Since‚ the results of the surgery greatly depend upon the skill of the hair transplant expert‚ it is a must that you invest some time and efforts to research for the best hair transplant clinic in your area. The next step is to schedule a preliminary meeting with hair transplant expert. During this meeting‚ the doctor will try to assess the causes behind your hair loss

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    Data Mining

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    Chapter 1 Exercises 1. What is data mining? In your answer‚ address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead‚ the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus‚ data mining can be viewed as the result of

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    Data Analysis

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    c. ratio scale d. interval scale 2. Data obtained from a nominal scale a. must be alphabetic b. can be either numeric or nonnumeric c. must be numeric d. must rank order the data 3. In a post office‚ the mailboxes are numbered from 1 to 4‚500. These numbers represent a. qualitative data b. quantitative data c. either qualitative or quantitative data d. since the numbers are sequential‚ the data is quantitative 4. A tabular summary of a set of data showing the fraction of the total number

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    Secondary data

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    Secondary data refers to the data which an investigator does not collect himself for his purpose rather he obtains them from some other source‚ agency or office. In other words‚ this data has already been collected by some other source and an investigator makes use of it for his purpose. Secondary data is different from primary data on the basis of the sources of their collection. The difference between the two is relative - data which is primary at one place become secondary at another place.

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    Data Mining

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    Data Mining DeMarcus Montgomery Dr. Janet Durgin CIS 500 June 9‚ 2013 Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model‚ which has‚ in turn been trained over your data‚ learning from the experience

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