Chapter 3 – Data Visualization Chapter 4 – Summary Statistics Data Mining for Business Intelligence Shmueli‚ Patel & Bruce © Galit Shmueli and Peter Bruce 2010 Data Visualization • “A picture is worth a thousand words” • Data visualization and summary statistics help condense data • Effective presentation • Supports data cleaning (identify missing values‚ outliers‚ incorrect values‚ duplicates) and exploring (combine some groups) • Helps identify suitable variables • Mandatory initial step for
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Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture‚ curation‚ storage search‚ sharing‚ transfer‚ analysis and visualization. At multiple TERABYTES in size‚ the text and images of Wikipedia are a classic example of big data. As of 2012‚ limits on the size of data sets that
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Oracle Fusion Applications Using External Data Integration Services Table of Contents Introduction 4 External Data Integration Services: Overview 4 Integration Points to consider 5 Locating File Import Templates: Explained 5 Prepare Data Files 6 Data Integration using Manual Flow 7 File for Import and Export: Highlights 7 File for Import and Export: Explained 8 Load Interface File for Import Process 10 Importing Data into Application Tables: Procedure 11 Flow Automation using Web Service
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Introduction Big Data is indeed a better idea. Every day‚ we create 2.5 quintillion bytes of data–so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: posts to social media sites‚ digital pictures and videos posted online‚ transaction records of online purchases‚ and from cell phone GPS signals to name a few. This data is big data. “Much like the scientific principle that we can’t observe a system without changing it‚ big data can’t
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DATA MINING REPORT A Comparison of K-means and DBSCAN Algorithm Data Mining with Iris Data Set Using K-Means Cluster method within Weak Data Mining Toolkit. Team Task ......................................................................................................................................... 3 1.0 Introduction ................................................................................................................................. 3 2.0 Related Works ................
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Gathering Research Data Introduction This following paper will be conducting research that is concerning the law enforcement and the jobs they have. The information that has been gathered will include job satisfaction and self-esteem. The goals of this research will be clearly stated and the appropriate methods for the research will be discussed. Gender diversity in the police workplace is another thing that will be discussed. The following question will be discussed: What is the
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Don’t forget to check out the Online Learning Center‚ www.mhhe.com/forouzan for additional resources! Instructors and students using Data Communications and Networking‚ Fourth Edition by Behrouz A. Forouzan will find a wide variety of resources available at the Online Learning Center‚ www.mhhe.comlforouzan Instructor Resources Instructors can access the following resources by contacting their McGraw-Hill Representative for a secure password. PowerPoint Slides. Contain figures‚ tables‚ highlighted
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Analyzing Data IT206 September 2‚ 2011 Don Shultz Analyzing Data The five basic steps that are required for analyzing data using Microsoft Access according to the article by Samuels and Wood (2007. The steps are to gather the data‚ create a database‚ edit and validate data‚ connect data files‚ and perform queries. The first step is to determine exactly what analyzes you want to perform and ensure that you gather all that is needed. Keep in mind to import into Access it has to be formatted
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Chapter 12 Data Envelopment Analysis Data Envelopment Analysis DEA is an increasingly popular management tool. This write-up is an introduction to Data Envelopment Analysis DEA for people unfamiliar with the technique. For a more in-depth discussion of DEA‚ the interested reader is referred to Seiford and Thrall 1990 or the seminal work by Charnes‚ Cooper‚ and Rhodes 1978 . DEA is commonly used to evaluate the e ciency of a number of producers. A typical statistical approach is characterized
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1. ------------------------------------------------- Types of searching 2.1 Binary search tree In computer science‚ a binary search tree (BST) is a node based binary tree data structure which has the following properties: * The left subtree of a node contains only nodes with keys less than the node ’s key. * The right subtree of a node contains only nodes with keys greater than the node ’s key. * Both the left and right subtrees must also be binary search trees. From the
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