university CASE STUDY OF DATA MINING Summitted by Jatin Sharma Roll no -32. Reg. no 10802192 A case study in Data Warehousing and Data mining Using the SAS System. Data Warehouses The drop in price of data storage has given companies willing to make the investment a tremendous resource: Data about their customers
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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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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 INTEGRATION Data integration involves combining data residing in different sources and providing users with a unified view of these data. This process becomes significant in a variety of situations‚ which include both commercial (when two similar companies need to merge their databases and scientific (combining research results from different bioinformatics repositories‚ for example) domains. Data integration appears with increasing frequency as the volume and the need to share existing data explodes
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Introduction The experience of focus group and semi-structured interview were gained during my data collection research. I conducted one focus group and one semi-structured interviews‚ due to participants time limit and busy schedule I was not possible to conduct more interviews. I have designed the interview procedure including questions prepared for each interview to capture different group and individual. I have given participants consent form to sign and ask for their permission to audio tape
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4V of Big Data? Imagine all the information you alone generate each time you swipe your credit card‚ post to social media‚ drive your car‚ leave a voicemail‚ or visit a doctor. Now try to imagine your data combined with the data of all humans‚ corporations‚ and organizations in the world! From healthcare to social media‚ from business to the auto industry‚ humans are now creating more data than ever before. volume‚ velocity‚ variety‚ and veracity. Volume: Scale of Data Big data is big. It’s
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Turnage‚ Bonebright‚ Buhman‚ Flowers (1996) showed that untrained participants can listen to shapes. That is‚ they used data sonification – musical representation of two dimensional space‚ with pitch as the vertical dimension and time as the horizontal dimension – to present participants the visual and auditory representation of waveforms. In two conditions‚ they showed the participants could match one visual presentation to one of two auditory representations‚ or match one auditory presentation
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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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best alternative in the following: Q.1 In the relational modes‚ cardinality is termed as: (A) Number of tuples. (B) Number of attributes. (C) Number of tables. (D) Number of constraints. Ans: A Q.2 Relational calculus is a (A) Procedural language. (C) Data definition language. Ans: B Q.3 The view of total database content is (A) Conceptual view. (C) External view. Ans: A Q.4 Cartesian product in relational algebra is (A) a Unary operator. (B) a Binary operator. (C) a Ternary operator. (D) not defined
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discussed and all concluded that data analysis methods help us understand facts‚ observe patterns‚ formulate explanations‚ and try out the hypotheses. Not only does it help us understand facts‚ but they we also discovered that data analysis is used in science and business‚ and even administration and policy-making processes. We’ve found out the data analysis can be carried out in all fields‚ including medicine and social sciences. Once an analysis is conducted the data that is carried out is documented
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