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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............................................................................... 1 1.3 Problem statement ................................................................................................................ 2 1.4 Assumption .......................................................................................................................... 2 2. Online Shopping System Requirement Analysis..................................................................... 2 2.1 Requirement
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Table of Contents 1.0 Introduction 2 2.0 Problem Statement 3 3.0 Objectives 4 4.0 Methods 5 4.1 Web Browser Speed Test 5 4.2 Web Browser Internet Protection 5 4.3 Web Browser Most Simplest Interface. 5 4.4 Web Browser User Rating 6 4.5 The Most Stable Web Browser 6 4.6 The Most Suitable Web Browser For All Platforms. 6 5.0 Results 7 5.1 Result For Web Browser Speed Test 7 5.2 Result For Web Browser Internet Protection 8 5.3 Result For Web Browser Simplest Interface 8
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Q) What are Secondary Data? Secondary Data Secondary data is information gathered for purposes other than the completion of a research project. Data previously collected by someone else‚ possibly for some other purpose that can be used later for making decisions if found suitable for the purpose‚ other than the original one. Secondary data can be acquired from the internal records of the organization‚ their departments‚ subsidiaries or sister organizations and also from external sources‚ such
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An Oracle White Paper July 2010 Data Masking Best Practices Oracle White Paper—Data Masking Best Practices Executive Overview ........................................................................... 1 Introduction ....................................................................................... 1 The Challenges of Masking Data ....................................................... 2 Implementing Data Masking .............................................................. 2
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Audit and organize the data. Understanding your data before cleaning improves the efficiency of your project and reduces the time and cost of data cleaning. Understand the purpose‚ location‚ flow‚ and workflows of your data before you start. Document data quality requirements and define rules for measuring quality. Create a reference for success‚ and targets to keep the project in check along the way. Set statistical checks on the data‚ and set a standard of quality control and completeness. Create
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an era of big data‚ this data-driven world has the potential to improve the efficiencies of enterprises and improve the quality of our lives; however‚ there are a number of challenges that must be addressed to allow us to exploit the full potential of big data. This paper focuses on challenges faced by online retailers when making use of big data. With the provided examples of online retailers Amazon and eBay‚ this paper addressed the key challenges of big data analytics including data capture and
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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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Qualitative Analysis Lab Solubility Data Table Cations | Ag+ | Pb2+ | Cu2+ | Ni2+ | Ba2+ | NaCl | White ppt‚ AgCl(soluble in 12M HCl‚ soluble in sln of good complexing agent‚ 6M NH3) | White ppt‚ PbCl2(soluble in hot water‚ soluble in 12M HCl‚ soluble in sln of xs NaOH) | Soluble – no ppt | Soluble – no ppt | Soluble – no ppt | Na2CO3 | White ppt‚ Ag2CO3(soluble in 6M HCl‚ soluble in sln of good complexing agent) | White ppt‚ PbCO3(soluble in 6M HCl‚ soluble in sln of good complexing agent)
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Secondary Data Analysis-Literature Review In the article “Violence‚ Older Peers‚ and the Socialization of Adolescent Boys in Disadvantage Neighborhoods” David J. Harding stated that “most theoretical perspectives on neighborhood effects on youth assume that neighborhood context serves as a source of socialization‚ but the exact sources and processes underlying adolescent socialization in disadvantaged neighborhoods are largely unspecified and unelaborated”. What Harding is saying is that most adolescent
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