Book Image

Learning Tableau 10 - Second Edition

Book Image

Learning Tableau 10 - Second Edition

Overview of this book

Tableau has for some time been one of the most popular Business Intelligence and data visualization tools available. Why? Because, quite simply, it’s a tool that’s responsive to the needs of modern businesses. But it’s most effective when you know how to get what you want from it – it might make your business intelligent, but it isn’t going to make you intelligent… We’ll make sure you’re well prepared to take full advantage of Tableau 10’s new features. Whether you’re an experienced data analyst that wants to explore 2016’s new Tableau, or you’re a beginner that wants to expand their skillset and bring a more professional and sharper approach to their organization, we’ve got you covered. Beginning with the fundamentals, such as data preparation, you’ll soon learn how to build and customize your own data visualizations and dashboards, essential for high-level visibility and effective data storytelling. You’ll also find out how to so trend analysis and forecasting using clustering and distribution models to inform your analytics. But it’s not just about you – when it comes to data it’s all about availability and access. That’s why we’ll show you how to share your Tableau visualizations. It’s only once insights are shared and communicated that you – and your organization – will start making smarter and informed decisions. And really, that’s exactly what this guide is for.
Table of Contents (17 chapters)
Learning Tableau 10 Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface

Summary


Up until this chapter, we'd looked at data which was, for the most part, well-structured and easy to use. In this chapter, we considered what constitutes good structure and ways to deal with poor data structure. Good structure consists of data that has a meaningful level of detail and which has measures that match that level of detail. When measures are spread across multiple columns, we get data that is wide instead of tall.

You've got some experience now in applying various techniques to deal with data that has the wrong shape or has measures at the wrong level of detail. Tableau gives us the power and flexibility to deal with some of these structural issues, but it is often preferable to fix data structure at the source.

In the next chapter, we'll continue looking at some advanced and powerful techniques. These will be exciting and fun. Instead of looking at how to fix problems, we'll look at some tips and tricks to expand your creativity and take Tableau to the next level!