Book Image

Tableau 10 Business Intelligence Cookbook

By : Donabel Santos, Paul Banoub
Book Image

Tableau 10 Business Intelligence Cookbook

By: Donabel Santos, Paul Banoub

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.

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Tableau 10 Business Intelligence Cookbook
Donabel Santos | Paul Banoub
Nov, 2016 | 476 pages
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Table of Contents (17 chapters)
Tableau 10 Business Intelligence Cookbook
Tableau 10 Business Intelligence Cookbook
Credits
Credits
About the Author
About the Author
Acknowledgements
Acknowledgements
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Basic Charts
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
2
Advanced Charts
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
3
Interactivity
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
4
Dashboards and Story Points
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
5
Maps and Geospatial Visualization
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
6
Analytics
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
7
Data Preparation
Data Preparation
Introduction
Using the Data Interpreter and pivot
Using the legacy Jet driver
Using schema.ini to resolve data type issues
Pivoting columns
Using union
Using join
Using blend
Calculated Fields Primer
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
Resources
Data sources for recipes in this book
Articles and white papers
Blogs and additional resources
Index
Index

Performing linear regression with R

Linear regression is a common technique to find the best fit straight line in a scatter plot. The resulting line can help in predictive analysis.

In this recipe, we will add trend lines to CO2 Emission graphs using R:

Getting ready

This recipe has a few prerequisites before it can be followed:

  1. Install R. The R Project for Statistical Computing website is https://www.r-project.org/.

  2. Optionally, install RStudio from https://www.rstudio.com/, which is an integrated environment for R.

  3. Install the Rserve package by running the following in R:

      install.packages("Rserve"); 
  library(Rserve);
run.Rserve();

  4. You will get a message that says the connection is blocked:

  5. Go to Help, and under Settings and Performance, select Manage External Service Connection...:

  6. Type localhost for the Server:, and leave the Port/API Key: to 6311. Test the connection, and ensure you get a successful connection message before proceeding:

Once R is ready and connected, you may proceed with the...

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