آماده‌سازی داده‌های خود برای تبلو: راهنمای عملی برای ابزار آماده‌سازی داده‌های تبلو

Focus on the most important and most often overlooked factor in a successful Tableau project—data. Without a reliable data source, you will not achieve the results you hope for in Tableau. This book does more than teach the mechanics of data preparation. It teaches you: how to look at data in a new way, to recognize the most common issues that hinder analytics, and how to mitigate those factors one by one. Tableau can change the course of business, but the old adage of "garbage in, garbage out" is the hard truth that hides behind every Tableau sales pitch. That amazing sales demo does not work as well with bad data. The unfortunate reality is that almost all data starts out in a less-than-perfect state. Data prep is hard. Traditionally, we were forced into the world of the database where complex ETL (Extract, Transform, Load) operations created by the data team did all the heavy lifting for us. Fortunately, we have moved past those days. With the introduction of the Tableau Data Prep tool you can now handle most of the common Data Prep and cleanup tasks on your own, at your desk, and without the help of the data team. This essential book will guide you through: • The layout and important parts of the Tableau Data Prep tool • Connecting to data • Data quality and consistency • The shape of the data. Is the data oriented in columns or rows? How to decide? Why does it matter? • What is the level of detail in the source data? Why is that important? • Combining source data to bring in more fields and rows • Saving the data flow and the results of our data prep work • Common cleanup and setup tasks in Tableau Desktop What You Will Learn: • Recognize data sources that are good candidates for analytics in Tableau • Connect to local, server, and cloud-based data sources • Profile data to better understand its content and structure • Rename fields, adjust data types, group data points, and aggregate numeric data • Pivot data • Join data from local, server, and cloud-based sources for unified analytics • Review the steps and results of each phase of the Data Prep process • Output new data sources that can be reviewed in Tableau or any other analytics tool Who This Book Is For: Tableau Desktop users who want to: connect to data, profile the data to identify common issues, clean up those issues, join to additional data sources, and save the newly cleaned, joined data so that it can be used more effectively in Tableau Table of Contents 6 About the Authors 11 About the Technical Reviewer 12 Foreword 13 Chapter 1: What Is ETL? 16 Extract 16 Transform 17 Load 17 Chapter 2: About the Demo Data 19 ZTCA to Census Tract 19 US_A.CSV 20 GEOCORR Education Data by State 21 US Population Density and Unemployment by Zip Code 22 Part I: Extract 24 Chapter 3: Connecting to Data 25 Working with Server-Based Data Sources 26 Connecting to SQL Server 26 Initial SQL (Running SQL on Connection) 28 Working with Tableau Data Extracts 31 Working with File-Based Data Sources 32 Connecting to Microsoft Access 32 Connecting to Microsoft Excel 34 Connecting to PDF Files 36 Connecting to Text Files 36 Summary 37 Chapter 4: UNION Joins 39 Exercise 4.1: Union Join 39 The Data Preview Pane 47 Data Types 48 Changes 50 Reviewing the Union Step 50 Union Join the Easy Way 53 Exercise 4.2 53 Exercise 4.3 59 Which Is Better? 61 Summary 62 Chapter 5: Joins 64 What Is a Table? 64 Equijoins 65 Join Types 66 Inner Joins 66 Left Joins 66 Right Joins 67 Outer Joins 67 The Shape of Your Data 68 Exercise 5.1: Joins 69 Missing Data 78 Finding Missing Records 79 Bringing It All Together 82 But Wait, There’s More! 85 Summary 87 Part II: Transform 88 Audit 88 Clean 88 Group and Replace 88 Aggregate 89 Pivot 89 Chapter 6: Audit 90 Exercise 6.1: Connect to Data 90 Summary 100 Chapter 7: Cleaning 101 Exercise 7.1: Add Step 101 Exercise 7.2: General Cleanup 104 Merge and Clean 104 Make the Data More Consistent 109 Split 114 Exercise 7.3: Split 115 Recommendations 118 Handle NULL Values 125 Filtering Records 126 Summary 129 Chapter 8: Group and Replace 130 Manual Selection 131 Pronunciation 135 Common Characters 136 Spelling 138 Summary 138 Chapter 9: Aggregate 139 Aggregating Data 140 Summary 143 Chapter 10: Pivoting Data 144 Pivot 145 UnPivot 153 Summary 155 Part III: Load 156 Chapter 11: Output 157 Exercise 11.1: Simple Output 157 Summary 162 Appendix A: Preparing Data IN Tableau 163 Tableau Builder Data Prep Checklist 163 Sample Data 164 Filter 165 Hide Fields 168 Rename 170 Pivot 170 Split 172 Alias Contents 173 Data Types 176 Data Roles 177 Defaults 180 Strings 180 Colors 180 Shapes 181 Sort 182 Numbers 184 Number Format 184 Default Aggregation 185 Dates 186 Fiscal Year Start 187 Custom Date Format 187 Custom Date 189 Hierarchies 191 Groups 192 Comments 194 Organize Dimensions and Measures 196 Calculated Fields 197 Live or Extract 198 Tableau Data Server 198 Saved Data Sources 199 Save to Extract 200 Summary 203 Index 204 Focus on the most important and most often overlooked factor in a successful Tableau project-- data. Without a reliable data source, you will not achieve the results you hope for in Tableau. This book does more than teach the mechanics of data preparation. It teaches you: how to look at data in a new way, to recognize the most common issues that hinder analytics, and how to mitigate those factors one by one. Tableau can change the course of business, but the old adage of "garbage in, garbage out" is the hard truth that hides behind every Tableau sales pitch. That amazing sales demo does not work as well with bad data. The unfortunate reality is that almost all data starts out in a less-than-perfect state. Data prep is hard. Traditionally, we were forced into the world of the database where complex ETL (Extract, Transform, load) operations created by the data team did all the heavy lifting for us. Fortunately, we have moved past those days. With the introduction of the Tableau Data Prep tool you can now handle most of the common Data Prep and cleanup tasks on your own, at your desk, and without the help of the data team. This essential book will guide you through: The layout and important parts of the Tableau Data Prep tool ; Connecting to data ; Data quality and consistency ; The shape of the data. is the data oriented in columns or rows? How to decide? Why does it matter? ; What is the level of detail in the source data? Why is that important? ; Combining source data to bring in more fields and rows ; Saving the data flow and the results of our data prep work ; Common cleanup and setup tasks in Tableau Desktop Front Matter ....Pages i-xvii What Is ETL? (Tim Costello, Lori Blackshear)....Pages 1-3 About the Demo Data (Tim Costello, Lori Blackshear)....Pages 5-9 Front Matter ....Pages 11-11 Connecting to Data (Tim Costello, Lori Blackshear)....Pages 13-26 UNION Joins (Tim Costello, Lori Blackshear)....Pages 27-51 Joins (Tim Costello, Lori Blackshear)....Pages 53-76 Front Matter ....Pages 77-78 Audit (Tim Costello, Lori Blackshear)....Pages 79-89 Cleaning (Tim Costello, Lori Blackshear)....Pages 91-119 Group and Replace (Tim Costello, Lori Blackshear)....Pages 121-129 Aggregate (Tim Costello, Lori Blackshear)....Pages 131-135 Pivoting Data (Tim Costello, Lori Blackshear)....Pages 137-148 Front Matter ....Pages 149-149 Output (Tim Costello, Lori Blackshear)....Pages 151-156 Back Matter ....Pages 157-202