{"product_id":"data-analysis-using-sql-and-excel-9781119021438","title":"Data Analysis Using SQL and Excel","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eA practical guide to data mining using SQL and Excel\u003c\/b\u003e  \u003cp\u003e\u003ci\u003eData Analysis Using SQL and Excel, 2nd Edition\u003c\/i\u003e shows you how to leverage the two most popular tools for data query and analysisSQL and Excelto perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You''ll learn the fundamental techniques before moving into the where and why of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2\/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eData Analysis Using SQL and Excel, 2nd \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003eForeword xxxiii\u003c\/p\u003e \u003cp\u003eIntroduction xxxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 A Data Miner Looks at SQL 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDatabases, SQL, and Big Data 2\u003c\/p\u003e \u003cp\u003ePicturing the Structure of the Data 6\u003c\/p\u003e \u003cp\u003ePicturing Data Analysis Using Dataflows 16\u003c\/p\u003e \u003cp\u003eSQL Queries 21\u003c\/p\u003e \u003cp\u003eSubqueries and Common Table Expressions Are Our Friends 36\u003c\/p\u003e \u003cp\u003eLessons Learned 47\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 What’s in a Table? Getting Started with Data Exploration 49\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat Is Data Exploration? 50\u003c\/p\u003e \u003cp\u003eExcel for Charting 51\u003c\/p\u003e \u003cp\u003eSparklines 65\u003c\/p\u003e \u003cp\u003eWhat Values Are in the Columns? 68\u003c\/p\u003e \u003cp\u003eMore Values to Explore—Min, Max, and Mode 79\u003c\/p\u003e \u003cp\u003eExploring String Values 81\u003c\/p\u003e \u003cp\u003eExploring Values in Two Columns 86\u003c\/p\u003e \u003cp\u003eFrom Summarizing One Column to Summarizing All Columns 90\u003c\/p\u003e \u003cp\u003eLessons Learned 96\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 How Different Is Different? 97\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBasic Statistical Concepts 98\u003c\/p\u003e \u003cp\u003eHow Different Are the Averages? 105\u003c\/p\u003e \u003cp\u003eSampling from a Table 110\u003c\/p\u003e \u003cp\u003eCounting Possibilities 115\u003c\/p\u003e \u003cp\u003eRatios and Their Statistics 128\u003c\/p\u003e \u003cp\u003eChi-Square 132\u003c\/p\u003e \u003cp\u003eWhat Months and Payment Types Have Unusual Affinities for Which Types of Products? 140\u003c\/p\u003e \u003cp\u003eLessons Learned 143\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Where Is It All Happening? Location, Location, Location 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eLatitude and Longitude 146\u003c\/p\u003e \u003cp\u003eCensus Demographics 160\u003c\/p\u003e \u003cp\u003eGeographic Hierarchies 172\u003c\/p\u003e \u003cp\u003eMapping in Excel 188\u003c\/p\u003e \u003cp\u003eLessons Learned 194\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 It’s a Matter of Time 197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDates and Times in Databases 198\u003c\/p\u003e \u003cp\u003eStarting to Investigate Dates 204\u003c\/p\u003e \u003cp\u003eHow Long Between Two Dates? 218\u003c\/p\u003e \u003cp\u003eYear-over-Year Comparisons 229\u003c\/p\u003e \u003cp\u003eCounting Active Customers by Day 239\u003c\/p\u003e \u003cp\u003eSimple Chart Animation in Excel 247\u003c\/p\u003e \u003cp\u003eLessons Learned 254\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 How Long Will Customers Last? Survival Analysis to Understand Customers and Their Value 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBackground on Survival Analysis 256\u003c\/p\u003e \u003cp\u003eThe Hazard Calculation 260\u003c\/p\u003e \u003cp\u003eSurvival and Retention 269\u003c\/p\u003e \u003cp\u003eComparing Different Groups of Customers 280\u003c\/p\u003e \u003cp\u003eComparing Survival over Time 287\u003c\/p\u003e \u003cp\u003eImportant Measures Derived from Survival 293\u003c\/p\u003e \u003cp\u003eUsing Survival for Customer Value Calculations 298\u003c\/p\u003e \u003cp\u003eForecasting 308\u003c\/p\u003e \u003cp\u003eLessons Learned 314\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Factors Affecting Survival: The What and Why of Customer Tenure 315\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhich Factors Are Important and When 316\u003c\/p\u003e \u003cp\u003eLeft Truncation 328\u003c\/p\u003e \u003cp\u003eTime Windowing 336\u003c\/p\u003e \u003cp\u003eCompeting Risks 342\u003c\/p\u003e \u003cp\u003eBefore and After 353\u003c\/p\u003e \u003cp\u003eLessons Learned 366\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Customer Purchases and Other Repeated Events 367\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIdentifying Customers 368\u003c\/p\u003e \u003cp\u003eRFM Analysis 393\u003c\/p\u003e \u003cp\u003eWhich Households Are Increasing Purchase Amounts Over Time? 404\u003c\/p\u003e \u003cp\u003eTime to Next Event 416\u003c\/p\u003e \u003cp\u003eLessons Learned 420\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 What’s in a Shopping Cart? Market Basket Analysis 421\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExploring the Products 422\u003c\/p\u003e \u003cp\u003eProducts and Customer Worth 437\u003c\/p\u003e \u003cp\u003eProduct Geographic Distribution 448\u003c\/p\u003e \u003cp\u003eWhich Customers Have Particular Products? 451\u003c\/p\u003e \u003cp\u003eLessons Learned 463\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Association Rules and Beyond 465\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eItem Sets 466\u003c\/p\u003e \u003cp\u003eThe Simplest Association Rules 480\u003c\/p\u003e \u003cp\u003eOne-Way Association Rules 483\u003c\/p\u003e \u003cp\u003eTwo-Way Associations 489\u003c\/p\u003e \u003cp\u003eExtending Association Rules 499\u003c\/p\u003e \u003cp\u003eLessons Learned 506\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Data Mining Models in SQL 507\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction to Directed Data Mining 508\u003c\/p\u003e \u003cp\u003eLook-Alike Models 515\u003c\/p\u003e \u003cp\u003eLookup Model for Most Popular Product 522\u003c\/p\u003e \u003cp\u003eLookup Model for Order Size 528\u003c\/p\u003e \u003cp\u003eLookup Model for Probability of Response 534\u003c\/p\u003e \u003cp\u003eNaive Bayesian Models (Evidence Models) 546\u003c\/p\u003e \u003cp\u003eLessons Learned 559\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 The Best-Fit Line: Linear Regression Models 561\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Best-Fit Line 562\u003c\/p\u003e \u003cp\u003eMeasuring Goodness of Fit Using R\u003csup\u003e2\u003c\/sup\u003e 581\u003c\/p\u003e \u003cp\u003eDirect Calculation of Best-Fit Line Coefficients 584\u003c\/p\u003e \u003cp\u003eWeighted Linear Regression 592\u003c\/p\u003e \u003cp\u003eMore Than One Input Variable 600\u003c\/p\u003e \u003cp\u003eLessons Learned 607\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Building Customer Signatures for Further Analysis 609\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat Is a Customer Signature? 610\u003c\/p\u003e \u003cp\u003eDesigning Customer Signatures 617\u003c\/p\u003e \u003cp\u003eOperations to Build Customer Signatures 622\u003c\/p\u003e \u003cp\u003eExtracting Features 639\u003c\/p\u003e \u003cp\u003eSummarizing Customer Behaviors 644\u003c\/p\u003e \u003cp\u003eLessons Learned 653\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Performance Is the Issue: Using SQL Effectively 655\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eQuery Engines and Performance 656\u003c\/p\u003e \u003cp\u003eConsiderations When Thinking About Performance 660\u003c\/p\u003e \u003cp\u003ePerformance: Its Meaning and Measurement 663\u003c\/p\u003e \u003cp\u003ePerformance Improvement 101 665\u003c\/p\u003e \u003cp\u003eUsing Indexes Effectively 668\u003c\/p\u003e \u003cp\u003eWhen OR Is a Bad Thing 683\u003c\/p\u003e \u003cp\u003ePros and Cons: Different Ways of Expressing the Same Thing 686\u003c\/p\u003e \u003cp\u003eWindow Functions 694\u003c\/p\u003e \u003cp\u003eLessons Learned 701\u003c\/p\u003e \u003cp\u003eAppendix Equivalent Constructs Among Databases 703\u003c\/p\u003e \u003cp\u003eIndex 731\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406967939415,"sku":"9781119021438","price":37.05,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119021438.jpg?v=1730497727","url":"https:\/\/bookcurl.com\/products\/data-analysis-using-sql-and-excel-9781119021438","provider":"Book Curl","version":"1.0","type":"link"}