Tableau 10 Business Intelligence Cookbook

Tableau 10 Business Intelligence Cookbook

By : Donabel Santos, Paul Banoub

Buy this Book

Tableau 10 Business Intelligence Cookbook

By: Donabel Santos, Paul Banoub

Buy this Book

Overview of this book

Tableau is a software tool that can speed up data analysis through its rich visualization capabilities, and help uncover insights for better and smarter decision making. This book is for the business, technology, data and analytics professionals who use and analyze data and data-driven approaches to support business operations and strategic initiatives in their organizations. This book provides easy-to-follow recipes to get the reader up and running with Tableau 10, and covers basic to advanced use cases and scenarios. The book starts with building basic charts in Tableau and moves on to building more complex charts by incorporating different Tableau features and interactivity components. There is an entire chapter dedicated to dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. By the end of this book, you’ll have gained confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau.

Tableau 10 Business Intelligence Cookbook

Credits

About the Author

Acknowledgements

About the Reviewer

www.PacktPub.com

Preface

Free Chapter

Basic Charts

Introduction

Creating a bar chart

Creating a stacked bar chart

Creating a line chart

Creating a scatter plot

Creating a heat map

Creating a text table (crosstab)

Creating a highlight table

Creating an area chart

Creating a pie chart

Creating a bubble chart

Creating a word cloud

Creating a tree map

Advanced Charts

Introduction

Creating a histogram

Creating a small multiple chart

Creating a shared axis chart

Creating a combo chart (dual axis chart)

Creating a bullet chart

Creating a bar in bar chart

Creating a donut chart

Creating a unit chart

Creating a box and whisker chart

Creating a sparkline with indicators

Creating a KPI text table

Creating a waterfall chart

Creating a population pyramid

Interactivity

Introduction

Creating a motion chart

Creating a dynamic column/row trellis chart

Creating a top/bottom N filter

Comparing one to everything else

Dynamically displaying dimensions

Dynamically displaying and sorting measures

Creating a custom date period filter

Dashboards and Story Points

Introduction

Creating a filter action

Creating a highlight action

Creating a URL action

Creating an Infographic-like dashboard

Creating story points

Maps and Geospatial Visualization

Introduction

Adding data layers to map

Creating custom territories

Working with Web Map Service (WMS)

Using path to display movement in map

Mapping custom polygons

Importing custom geocoding

Using a custom image background

Analytics

Introduction

Adding a constant line

Adding a trend line

Using a reference line

Adding a reference band

Performing cluster analysis

Visualizing forecast

Performing linear regression with R

Data Preparation

Introduction

Using the Data Interpreter and pivot

Using the legacy Jet driver

Using schema.ini to resolve data type issues

Calculated Fields Primer

Different ways to create calculated fields

Calculated field window

Functions in Tableau

Function syntax

Word of caution

Different types of calculated fields

Dealing with NULLs

Tidbits

Conclusion

Resources

Data sources for recipes in this book

Articles and white papers

Blogs and additional resources

Index

Customer Reviews

5 star

4 star

3 star

2 star

1 star

Introduction

In a perfect world, we wouldn't even need to have this chapter. In a perfect world, we would have perfect, clean data that we could easily analyze in Tableau. But, alas, in reality, the data that we need to use will most likely need to be cleaned, transformed, and managed before we can effectively use it in Tableau.

There are tools that exclusively help clean and re-shape data. Many refer to these as ETL (Extract, Transform, and Load) tools. While Tableau is not an ETL tool, it has the ability to help clean or prepare data if it is not possible to clean or prepare it at the data source. Calculated fields, discussed in Appendix A, Calculated Fields Primer, are also invaluable in the data cleaning process.

Tableau 10 Business Intelligence Cookbook

By : Donabel Santos, Paul Banoub

Tableau 10 Business Intelligence Cookbook

By: Donabel Santos, Paul Banoub

Overview of this book

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Current Title:

Tableau 10 Business Intelligence Cookbook

Introduction