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


Tableau provides an extensive set of features for adding value to your analysis. Trend lines allow you to more precisely identify outliers, determine which values fall within the predictions of certain models, and even make predictions of where measurements are expected. Tableau gives extensive visibility into trend models and even allows you to export data containing trend model predictions and residuals. Clusters enable you to find groups of related data points based on various factors. Distributions are useful for understanding a spread of values across a set of data. Forecasting allows for a complex model of trends and seasonality to predict future results. Having a good understanding of these tools will give you the ability to clarify and validate your initial visual analyses.

Next, we'll turn our attention back to the data. We considered very early on how to connect to data and we've been working with data ever since. However, we've spent most of our time working with clean...