glimpse of Big Data Jan. 2013 What is big data? “Big data is not a precise term; rather it’s a characterization of the never ending accumulation of all kinds of data‚ most of it unstructured. It describes data sets that are growing exponentially and that are too large‚ too raw or too unstructured for analysis using relational database techniques. Whether terabytes or petabytes‚ the precise amount is less the issue than where the data ends up and how it is used.”------Cite from EMC’s report
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Data Mining On Medical Domain Smita Malik‚ Karishma Naik‚ Archa Ghodge‚ Shivani Gaunker Shree Rayeshwar Institute of Engineering & Information Technology Shiroda‚ Goa‚ India. Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com Abstract-The successful application of data mining in highly visible fields like retail‚ marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries
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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 Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus‚ data mining should have been more appropriately named “knowledge mining from data‚” which is unfortunately somewhat long. Knowledge mining‚ a shorter term‚ may not
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this 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. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed from databases
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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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Using the Standard Deviation You made a number of observations about the data sets for the school activities. You used mean and median to measure the center of the data‚ and you used the interquartile range (IQR) to measure the spread. When outliers are present‚ the median and IQR are used to measure center and spread because they are unaffected by extreme values. When the data appears to be symmetric and there are no known outliers‚ the mean and standard deviation (another measure of spread)
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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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and Kimball’s definition of Data Warehousing. Bill Inmon advocates a top-down development approach that adapts traditional relational database tools to the development needs of an enterprise wide data warehouse. From this enterprise wide data store‚ individual departmental databases are developed to serve most decision support needs. Ralph Kimball‚ on the other hand‚ suggests a bottom-up approach that uses dimensional modeling‚ a data modeling approach unique to data warehousing. Rather than building
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UNIVERSITY‚ ISLAMABAD (Department of Educational Planning Policy Studies & Leadership) WARNING 1. PLAGIARISM OR HIRING OF GHOST WRITER(S) FOR SOLVING THE ASSIGNMENT(S) WILL DEBAR THE STUDENT FROM AWARD OF DEGREE/CERTIFICATE‚ IF FOUND AT ANY STAGE. 2. SUBMITTING ASSIGNMENTS BORROWED OR STOLEN FROM OTHER(S) AS ONE’S OWN WILL BE PENALIZED AS DEFINED IN “AIOU PLAGIARISM POLICY”. NOTE: Before attempting assignments‚ please read the following instructions: 1. All questions are compulsory. 2
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