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

关注一个成功的Tableau项目中最重要也是最常被忽视的因素--数据。如果没有一个可靠的数据源，你将无法在Tableau中实现你所希望的结果。本书不仅仅是教授数据准备的机制。它教你：如何以一种新的方式看待数据，认识阻碍分析的最常见的问题，以及如何逐一缓解这些因素。Tableau可以改变业务的进程，但 "垃圾进，垃圾出 "这句老话是隐藏在每个Tableau推销背后的硬道理。那个惊人的销售演示在糟糕的数据下并不奏效。不幸的现实是，几乎所有的数据一开始都是不太完美的。数据预处理是很难的。

传统上，我们被迫进入数据库的世界，由数据团队创建的复杂的ETL（提取、转换、加载）操作为我们完成了所有繁重的工作。幸运的是，我们已经走过了那些日子。随着Tableau数据准备工具的引入，你现在可以在自己的办公桌上处理大多数常见的数据准备和清理任务，而无需数据团队的帮助。这本必不可少的书将指导你完成。

- Tableau数据准备工具的布局和重要部分

- 连接到数据

- 数据质量和一致性

- 数据的形状。数据是以列还是行为导向？如何决定？为什么会有这样的问题？

- 源数据的详细程度是什么？为什么这很重要？

- 合并源数据以带来更多的字段和行

- 保存数据流和我们数据准备工作的结果

- Tableau Desktop中常见的清理和设置任务

你将会学到什么？

- 识别那些适合在Tableau中进行分析的数据源

- 连接到本地、服务器和基于云的数据源

- 对数据进行剖析以更好地了解其内容和结构

- 重命名字段，调整数据类型，对数据点进行分组，并汇总数字数据

- 透视数据

- 将来自本地、服务器和云端的数据结合起来，进行统一分析

- 回顾数据准备过程中的每个阶段的步骤和结果

- 输出可在Tableau或任何其他分析工具中审查的新数据源

本书适用对象。希望实现以下目标的Tableau Desktop用户：连接数据、对数据进行剖析以识别常见的问题、清理这些问题、连接到其他数据源，并保存新清理的、连接的数据，以便在Tableau中更有效地使用。