Prepare Your Data for Tableau (eBook)

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

Tim Costello is a senior data architect focused on the data warehouse life cycle, including the design of complex ETL (Extract, Transform, Load) processes, data warehouse design and visual analytics with Tableau. He has been actively involved with Tableau for almost 10 years. He founded the Dallas/Fort Worth Tableau user group. He has delivered hundreds of Tableau classes online and in person all over the USA and Canada.

When Tim isn't working with data, he is probably peddling his bicycle in circles around DFW airport in Dallas, Texas. He aspires to be a long distance rider and enjoys going on rides ranging over several days and hundreds of miles at a time.

Lori Blackshear is a senior business process architect and expert at facilitating meaningful and productive communication between business and technology groups. She has deep experience in healthcare (human and veterinary), software development, and research and development in support of emergency services.

Lori served as a paramedic in Fort Worth, Texas and Nashville, Tennessee before shifting careers to helping people solve problems with data. When Lori isn't pondering business processes, she is active in the Fort Worth Civic Orchestra (violin) and the East Fort Worth Community Jazz band (tenor saxophone).

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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 "e;garbage in, garbage out"e; 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 toolConnecting to dataData quality and consistencyThe 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 rowsSaving the data flow and the results of our data prep workCommon cleanup and setup tasks in Tableau DesktopWhat You Will LearnRecognize data sources that are good candidates for analytics in TableauConnect to local, server, and cloud-based data sourcesProfile data to better understand its content and structureRename fields, adjust data types, group data points, and aggregate numeric dataPivot dataJoin data from local, server, and cloud-based sources for unified analyticsReview the steps and results of each phase of the Data Prep processOutput new data sources that can be reviewed in Tableau or any other analytics toolWho This Book Is ForTableau 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