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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
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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
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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
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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
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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
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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
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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

Visualizing distributions

Often, simply understanding totals, sums, and even the breakdown of part-to-whole only gives you a piece of the overall picture. Many times, you'll want to understand where individual items fall within a distribution of all similar items.

You might find yourself asking questions like these:

  • How long do most of our patients stay in the hospital? Which patients fall outside the normal range?
  • What's the average life expectancy for components in a machine and which components fall above or below that average? Are there any components with extremely long or extremely short lives?
  • How far above or below "passing" were most students' test scores?

These questions all have similarities. In each case, you are asking for an understanding of how individuals (patients, components, and students) compared with each other. In each case, you most likely have a relatively high number of individuals. In data terms, you have a dimension (Patient, Component, and...

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Learning Tableau
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