Mastering Tableau 2021 [3 ed.] 9781800560741, 1800560745

2,893 949 93MB

English Pages [793] Year 2021

Mastering Tableau 2021 [3 ed.]
9781800560741, 1800560745

Author / Uploaded
Marleen Meier
David Baldwin

Table of contents :
Cover
Copyright
Foreword
Contributors
Table of Contents
Preface
Chapter 1: Getting Up to Speed – A Review of the Basics
Creating worksheets and dashboards
Creating worksheets
Creating a visualization
Beyond the default behavior
Show Me
Creating dashboards
Building a dashboard
Adding interactivity to a dashboard
Connecting Tableau to your data
Connecting to a file
Connecting to Tableau Server
Connecting to saved data sources
Measure Names and Measure Values
Measure Names and Measure Values shortcuts
Three essential Tableau concepts
Dimensions and measures
Row-level, aggregate-level, and table-level calculations
Continuous and discrete
Exporting data to other devices
Exporting data to a mobile phone
Tableau Mobile
Summary
Chapter 2: All About Data – Getting Your Data Ready
Understanding Hyper
The Tableau data-handling engine
Changing field attribution
Table calculation
Hyper takeaways
Data mining and knowledge discovery process models
Survey of the process models
CRISP-DM
CRISP-DM phases
Focusing on data preparation
Surveying data
Establishing null values
Extrapolating data
Cleaning messy data
Cleaning the data
Extracting data
Summary
Chapter 3: Tableau Prep Builder
Connecting to data
The Tableau Prep Builder GUI
Getting to know Tableau Prep Builder
Prepping data
Cleaning data
Unions and joins
Adding unions
Adding joins
Aggregating
Pivoting
Scripting
Additional options with Tableau Prep Builder
Insert flow
Incremental refresh
Tableau Prep Conductor
Exporting data
Summary
Chapter 4: All About Data – Joins, Blends, and Data Structures
Relationships
Joins
Join culling
Snowflaking
Join calculations
Spatial joins
Unions
Blends
Exploring the order of operations
Adding secondary dimensions
Introducing scaffolding
Understanding data structures
Summary
Chapter 5: Table Calculations
A definition and two questions
Introducing functions
Directional and non-directional table calculations
Exploring each unique table calculation function
Lookup and Total
Previous Value
Running
Window
First and Last
Index
Rank
Size
Application of functions
Building a playground
Partitioning and addressing with one dimension
Partitioning and addressing with two dimensions
Partitioning and addressing with three dimensions
Summary
Chapter 6: All About Data – Data Densification, Cubes, and Big Data
Using the OData connector
Introducing data densification
Domain completion
Deploying domain completion
The usefulness of domain completion
Removing unwanted domain completion
Domain padding
Deploying domain padding
The usefulness of domain padding
Problems of domain padding
Working with cubes
Data blending for continuous months
Data blending for hierarchies, aliasing, and grouping
Tableau and big data
Addressing Excel's row limitation
Massively parallel processing
Building a visualization with Google BigQuery
Summary
Chapter 7: Level of Detail Calculations
Introducing LOD calculations
Playground I: FIXED and EXCLUDE
Setting up the workbook
Understanding FIXED
Table-scoped expressions
Quick LOD calculations
Understanding EXCLUDE
Understanding Tableau's order of operations
Playground II: INCLUDE
Setting up the workbook
Understanding INCLUDE
Building practical applications with LODs
Using the LOD calculation FIXED
Using the LOD calculation INCLUDE
Using the LOD calculation EXCLUDE
Summary
Chapter 8: Beyond the Basic Chart Types
Improving popular visualizations
Bullet graphs
Using bullet graphs
Bullet graphs – beyond the basics
Pies and donuts
Pies and donuts on maps
Pies and donuts – beyond the basics
Pareto charts
Using Pareto charts
Pareto charts – beyond the basics
Custom background images
Creating custom polygons
Drawing a square around Null Island
Creating an interactive bookshelf using polygons
Analyzing a game of chess in Tableau
Creating an SVG file in Tableau
Creating a grid
Using a grid to generate a dataset
Visualizing a chess game
Creating polygons on a background image
Tableau extensions
Using Show me More
Einstein Discovery
Summary
Chapter 9: Mapping
Extending Tableau's mapping capabilities without leaving Tableau
Creating custom polygons
Polygons for Texas
Heatmaps
Dual axes and layering maps
Using dual axes
Adding map layers
Extending Tableau mapping with other technology
Using custom maps with a Web Map Service
Exploring Mapbox
Swapping maps
Summary
Chapter 10: Tableau for Presentations
Getting the best images out of Tableau
Tableau's native export capabilities
From Tableau to PowerPoint
Creating a template
Creating a dashboard for print
Semi-automating a PowerPoint presentation
Embedding Tableau in PowerPoint
Animating Tableau
Using an animation to export many images
Using an animation in Tableau to create an animation in PowerPoint
Story points and dashboards for presentations
Presentation resources
Summary
Chapter 11: Visualization Best Practices and Dashboard Design
Visualization design theory
Formatting rules
Keep the font choice simple
Use lines in order of visibility
Use bands in groups of three to five
Color rules
Keep colors simple and limited
Respect the psychological implications of colors
Be colorblind-friendly
Use pure colors sparingly
Choose color variations over symbol variation
Visualization type rules
Keep shapes simple
Use pie charts sparingly
Compromises
Making the dashboard simple and robust
Presenting dense information
Telling a story
Maximizing documentation on a dashboard
Keeping visualizations simple
Dashboard design
Dashboard layout
The golden ratio layout
The quad layout
The small multiple layout
Utilizing sheet swapping
Creating a collapsible menu
Dashboard best practices for user experience
Actions
Filter actions
Highlight actions
URL actions
Navigation actions
Parameter actions
Set actions
Export Dashboard Button
Item hierarchy
Used In
Summary
Chapter 12: Advanced Analytics
Visualizing world indices correlations
Plotting a scattergraph
Adding axis distributions
Adding a correlation matrix
Finalizing the dashboard
Geo-spatial analytics with Chicago traffic violations
Preparing the data
Building a map of intersections
Adding a corresponding heatmap worksheet
Finalizing the dashboard
Extending geo-spatial analytics with distance measures
Adding measure points to the map
Adding the distance line
Summary
Chapter 13: Improving Performance
Understanding the performance-recording dashboard
Hardware and on-the-fly techniques
Configuring auto updates
The Run Update feature
Small extracts
Connecting to data sources
Working efficiently with large data sources
Defining primary and foreign keys
Defining columns as NOT NULL
Indexing
Working with extracts
Constructing an extract
Aggregation
Optimizing extracts
Using filters wisely
Extract filters
Data source filters
Context filters
Dimension and measure filters
Table calculation filters
Using actions instead of filters
Efficient calculations
Prioritizing code values
Level-of-detail calculation or table calculations
Other ways to improve performance
Avoid overcrowding a dashboard
Fixing dashboard sizing
Setting expectations
Summary
Chapter 14: Interacting with Tableau Server/Online
Publishing a data source to Tableau Server
Tableau file types
Tableau data source
Tableau packaged data source
Tableau workbook
Tableau packaged workbook
Other file types
Tableau Server architecture
Approaches to avoid
Approaches to adopt
Web authoring
Editing an existing workbook with web authoring
Understanding the Tableau Server web authoring environment
Comparing Tableau Desktop and web authoring
Maintaining workbooks on Tableau Server
Revision history
User filters
Performance-recording dashboard
More Tableau Server settings and features
Features on the worksheet level
Features on the view level
Summary
Chapter 15: Programming Tool Integration
Integrating programming languages
R installation and integration
Implementing R functionality
Reproducing native Tableau functionality in R
Using R for regression calculations
Clustering in Tableau using R
Introducing quantiles
Performance challenges
Python installation and integration
Implementing Python functionality
Random and random normal
Generating random numbers
Random normal
Calculating sentiment analysis
Deploying models with TabPy
Predeployed TabPy functions
Summary
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Index