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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Data Collection: Data collection is the heart of any research. No study is complete without the data collection. This research also includes data collection and was done differently for different type of data. TYPES OF DATA Primary Data: For the purpose of collecting maximum primary data‚ a structured questionnaire was used wherein questions pertaining to the satisfaction level of the customer about pantaloons product(apparel)‚ the quality‚ color‚ variety of products‚ the availability of different
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DATA COMPRESSION The word data is in general used to mean the information in digital form on which computer programs operate‚ and compression means a process of removing redundancy in the data. By ’compressing data’‚ we actually mean deriving techniques or‚ more specifically‚ designing efficient algorithms to: * represent data in a less redundant fashion * remove the redundancy in data * Implement compression algorithms‚ including both compression and decompression. Data Compression
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Assignment #2 EC1204 Economic Data Collection and Analysis Student No. 110393693 Part 1: Question 2 From analysing the Data on the Scatter Plot the relationship between the GDP and the Population of Great Britain from 1999-2009 appears to be a moderate positive correlation relationship. Both variables are increasing at a similar rate and following a similar pattern which would indicate this relationship. This relationship would tend to be a positive one as more people are available to the
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Data Gathering ➢ used to discover business information details to define the information structure ➢ helps to establish the priorities of the information needs ➢ further leads to opportunities to highlight key issues which may cross functional boundaries or may touch on policies or the organization itself ➢ highlighting systems or enhancements that can quickly satisfy cross-functional information needs ➢ a complicated task especially in a large and complex system ➢ must
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Data Processing During the collection of data‚ our group noted the effect that temperature change had on aquatic macro invertebrates. Our data was collected from three different ponds amongst the Lake Harriet/Lake Calhoun vicinity. We took samples from the bird sanctuary pond‚ Lake Calhoun holding pond and the Lake Harriet duck area. Prior to our procedure‚ we measured the temperatures of each pond area. We used the low-temperature climate (bird sanctuary pond) to compare to the higher-temperature
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Data Tech‚ Inc. 2 Determine whether Jeff should give greater priority to a smaller facility with possibility of expansion or more into a larger facility immediately. According to Sliwinski and Gabryelczyk‚ facility management is a customer-oriented complete service‚ covering the comprehensive decision-making principles for optimum planning‚ usage and adaption of buildings
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November 2011 Security Techniques for Protecting Data in Cloud Computing Venkata Sravan Kumar Maddineni Shivashanker Ragi School of Computing Blekinge Institute of Technology SE - 371 79 Karlskrona Sweden i This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering. The thesis is equivalent to 40 weeks of full time studies. Contact Information: Author(s): Venkata
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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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Services E20-007 Data Science and Big Data Analytics Exam Exam Description Overview This exam focuses on the practice of data analytics‚ the role of the Data Scientist‚ the main phases of the Data Analytics Lifecycle‚ analyzing and exploring data with R‚ statistics for model building and evaluation‚ the theory and methods of advanced analytics and statistical modeling‚ the technology and tools that can be used for advanced analytics‚ operationalizing an analytics project‚ and data visualization techniques
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