LEADER 04134nam 22005295 450 001 9910369902603321 005 20230804142957.0 010 $a9781484254974 010 $a148425497X 024 7 $a10.1007/978-1-4842-5497-4 035 $a(CKB)5280000000190261 035 $a(MiAaPQ)EBC5997278 035 $a(DE-He213)978-1-4842-5497-4 035 $a(CaSebORM)9781484254974 035 $a(PPN)242821197 035 $a(OCoLC)1150901819 035 $a(OCoLC)on1150901819 035 $a(EXLCZ)995280000000190261 100 $a20191216d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPrepare Your Data for Tableau $eA Practical Guide to the Tableau Data Prep Tool /$fby Tim Costello, Lori Blackshear 205 $a1st ed. 2020. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2020. 215 $a1 online resource (207 pages) 300 $aIncludes index. 311 08$a9781484254967 311 08$a1484254961 327 $aChapter 1: What is ETL -- Chapter 2: About the Demo Data -- Chapter 3: Connecting to Data -- Chapter 4: UNION Joins -- Chapter 5: Joins -- Chapter 6: Audit -- Chapter 7: Cleaning -- Chapter 8: Group and Replace -- Chapter 9: Aggregate -- Chapter 10: Pivoting Data -- Chapter 11: Output -- Appendix 1: Preparing data IN Tableau. 330 $aFocus 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 You will: 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. 606 $aApplication software 606 $aComputer and Information Systems Applications 615 0$aApplication software. 615 14$aComputer and Information Systems Applications. 676 $a001.4226 700 $aCostello$b Tim$4aut$4http://id.loc.gov/vocabulary/relators/aut$0549088 702 $aBlackshear$b Lori$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910369902603321 996 $aPrepare Your Data for Tableau$92106213 997 $aUNINA