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  • Book Overview & Buying Learning Tableau
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Learning Tableau

Learning Tableau

By : Joshua N. Milligan
3.8 (22)
Buy this Book
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Learning Tableau

Learning Tableau

3.8 (22)
By: Joshua N. Milligan
Buy this Book

Overview of this book

If you want to understand your data using data visualization and don't know where to start, then this is the book for you. Whether you are a beginner or have years of experience, this book will help you to quickly acquire the skills and techniques used to discover, analyze, and communicate data visually. Some familiarity with databases and data structures is helpful, but not required.
Table of Contents (13 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Creating Your First Visualizations and Dashboard
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1. Creating Your First Visualizations and Dashboard
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Connecting to data in Access
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Foundations for building visualizations
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Visualizing data
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Bringing everything together in a dashboard
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Summary
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2. Working with Data in Tableau
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2. Working with Data in Tableau
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The Tableau paradigm
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Connecting to data
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Working with extracts instead of live connections
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Metadata and sharing data source connections
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Joins and blends
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Filtering data
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Summary
3
3. Moving from Foundational to Advanced Visualizations
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3. Moving from Foundational to Advanced Visualizations
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Comparing values across different dimensions
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Visualizing dates and times
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Relating parts of the data to the whole
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Visualizing distributions
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Visualizing multiple axes to compare different measures
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Summary
4
4. Using Row-level and Aggregate Calculations
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4. Using Row-level and Aggregate Calculations
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Creating and editing calculations
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Three levels of calculation
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Parameters
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Practical examples of calculations and parameters
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Ad hoc calculations
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Performance considerations
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Summary
5
5. Table Calculations
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5. Table Calculations
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An overview of table calculations
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Quick table calculations
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Scope and direction
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Addressing and partitioning
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Advanced table calculations
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Practical examples
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Summary
6
6. Formatting a Visualization to Look Great and Work Well
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6. Formatting a Visualization to Look Great and Work Well
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Formatting considerations
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How formatting works in Tableau
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Adding value to visualizations
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Summary
7
7. Telling a Data Story with Dashboards
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7. Telling a Data Story with Dashboards
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Dashboard objectives
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Example – is least profitable always unprofitable?
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How actions work
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Example – a regional scorecard
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Story points
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Summary
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8. Adding Value to Analysis – Trends, Distributions, and Forecasting
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8. Adding Value to Analysis – Trends, Distributions, and Forecasting
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Trends
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Distributions
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Forecasting
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Summary
9
9. Making Data Work for You
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9. Making Data Work for You
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Structuring data for Tableau
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Dealing with data structure issues
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An overview of advanced fixes for data problems
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Summary
10
10. Advanced Techniques, Tips, and Tricks
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10. Advanced Techniques, Tips, and Tricks
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Sheet swapping and dynamic dashboards
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Leveraging sets to answer complex questions
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Mapping techniques
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Using background images
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Summary
11
11. Sharing Your Data Story
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11. Sharing Your Data Story
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Presenting, printing, and exporting
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Sharing a workbook with users of Tableau Desktop or Tableau Reader
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Sharing data with users of Tableau Server, Tableau Online, and Tableau Public
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Summary
12
Index
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Index

Practical examples of calculations and parameters

Let's turn our attention to some practical examples of calculations. These will be examples of row-level and aggregate-level calculations. These are merely examples. The goal is to learn and understand what is possible with calculations. You will be able to build on these examples as you embark on your analysis and visualization.

Fixing data issues

Often data is not entirely clean. That is, it has problems that need to be corrected before much meaningful analysis can be accomplished. For example, dates may be incorrectly formatted or fields may contain a mix of numeric values and character codes that need to be separated into multiple fields. Calculated fields can often be used to fix these kinds of issues.

We will make use of the sample data introduced at the beginning of this chapter, which contained date values like this:

Start

End

03.17.2014

Oct-14

The original source was Excel and the start date was stored as a text value and the end...

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