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    Data Preprocessing

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    Data Preprocessing 3 Today’s real-world databases are highly susceptible to noisy‚ missing‚ and inconsistent data due to their typically huge size (often several gigabytes or more) and their likely origin from multiple‚ heterogenous sources. Low-quality data will lead to low-quality mining results. “How can the data be preprocessed in order to help improve the quality of the data and‚ consequently‚ of the mining results? How can the data be preprocessed so as to improve the efficiency and ease

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    Data Mining

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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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    Statistics and Data

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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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    Data Mining

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    Data Mining Assignment 4 Shauna N. Hines Dr. Progress Mtshali Info Syst Decision-Making December 7‚ 2012 Benefits of Data Mining Data mining is defined as “a process that uses statistical‚ mathematical‚ artificial intelligence‚ and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases‚ including data warehouses” (Turban & Volonino‚ 2011). The information identified using data mining includes patterns indicating trends‚ correlations

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    Data Quality

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    PRINCIPLES OF DATA QUALITY Arthur D. Chapman1 Although most data gathering disciples treat error as an embarrassing issue to be expunged‚ the error inherent in [spatial] data deserves closer attention and public understanding …because error provides a critical component in judging fitness for use. (Chrisman 1991). Australian Biodiversity Information Services PO Box 7491‚ Toowoomba South‚ Qld‚ Australia email: papers.digit@gbif.org 1 © 2005‚ Global Biodiversity Information Facility Material

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    Big Data

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    Networks Volvo utilized data mining in an effort to discover the unknown valuable relationships in the data collected and to assist in making early predictive information. It created a network of sensors and CPUs that were embedded throughout the cars and from which data was captured. Data was also captured from customer relationship systems (CRM)‚ dealership systems‚ product development and design systems and from the production floors in their factories. The terabytes of data collected was streamed

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    Mobile Application

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    Eco-System of the mobile application The quality or state of being mobile. The rising demand for mobile applications has taken mobile technology to a new level. As per In-Stat expects‚ mobile application downloads is expected to reach nearly 48 billion in 2015 and Forrester Research predicts the mobile app market to be worth $38 billion by 2015. It is a well known fact‚ that for businesses to succeed‚ partnership plays a vital role. Similar is the situation for mobile application development environment

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    Big Data

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    Big DataData Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse

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    Big Data

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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 processing

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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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