Book Image

Tableau 10 Complete Reference

By : Joshua N. Milligan, Tristan Guillevin
Book Image

Tableau 10 Complete Reference

By: Joshua N. Milligan, Tristan Guillevin

Overview of this book

Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You’ll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau. This Learning Path includes content from the following Packt products: • Learning Tableau 10 - Second Edition by Joshua N. Milligan • Getting Started with Tableau 2018.x by Tristan Guillevin
Table of Contents (20 chapters)
Title Page
About Packt
Deeper Analysis - Trends, Clustering, Distributions, and Forecasting

Overview of advanced fixes for data problems

In addition to the techniques previously mentioned in this chapter, there are some additional possibilities for dealing with data structure issues. It is outside the scope of this book to develop these concepts fully. However, if you have some familiarity with these approaches, you broaden your ability to deal with challenges as they arise.

  1. Custom SQL: This can be used in the data connection to resolve some data problems. Beyond giving a field for a cross database join, as we saw previously, custom SQL can be used to radically reshape the data retrieved from the source. Custom SQL is not an option for all data sources but is for many relational databases and for the legacy JET driver connections for Excel and text files. Consider a custom SQL script that takes the wide table of country populations mentioned earlier in this chapter and restructures it into a tall table:
        SELECT [Country Name],[1960] AS Population, 1960 AS Year