Mastering Tableau 2019.1 - Second Edition

Mastering Tableau 2019.1 - Second Edition

by Marleen Meier, David Baldwin
Released February 2019
Publisher(s): Packt Publishing
ISBN: 9781789533880

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Book description

Build, design and improve advanced business intelligence solutions using Tableau's latest features, including Tableau Prep, Tableau Hyper, and Tableau Server

Key Features

  • Master new features in Tableau 2019.1 to solve real-world analytics challenges
  • Perform Geo-Spatial Analytics, Time Series Analysis, and self-service analytics using real-life examples
  • Build and publish dashboards and explore storytelling using Python and MATLAB integration support

Book Description

Tableau is one of the leading business intelligence (BI) tools used to solve BI and analytics challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain.

This book is also the second edition of the popular Mastering Tableau series, with new features, examples, and updated code. The book covers essential Tableau concepts and its advanced functionalities. Using Tableau Hyper and Tableau Prep, you'll be able to handle and prepare data easily. You'll gear up to perform complex joins, spatial joins, union, and data blending tasks using practical examples. Following this, you'll learn how to perform data densification to make displaying granular data easier. Next, you'll explore expert-level examples to help you with advanced calculations, mapping, and visual design using various Tableau extensions. With the help of examples, you'll also learn about improving dashboard performance, connecting Tableau Server, and understanding data visualizations. In the final chapters, you'll cover advanced use cases such as Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics, and learn to connect Tableau to R, Python, and MATLAB.

By the end of this book, you'll have mastered the advanced offerings of Tableau and be able to tackle common and not-so-common challenges faced in the BI domain.

What you will learn

  • Get up to speed with various Tableau components
  • Master data preparation techniques using Tableau Prep
  • Discover how to use Tableau to create a PowerPoint-like presentation
  • Understand different Tableau visualization techniques and dashboard designs
  • Interact with the Tableau server to understand its architecture and functionalities
  • Study advanced visualizations and dashboard creation techniques
  • Brush up on powerful Self-Service Analytics, Time Series Analytics, and Geo-Spatial Analytics

Who this book is for

This book is designed for business analysts, BI professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.

Table of contents

  1. Title Page
  2. Copyright and Credits
    1. Mastering Tableau 2019.1 Second Edition
  3. About Packt
    1. Why subscribe?
    2. Packt.com
  4. Contributors
    1. About the authors
    2. About the reviewers
    3. Packt is searching for authors like you
  5. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
      1. Download the example code files
      2. Download the color images
      3. Conventions used
    4. Get in touch
      1. Reviews
  6. Section 1: Tableau Concepts, Basics
  7. Getting Up to Speed - A Review of the Basics
    1. Creating worksheets and dashboards
      1. Creating worksheets
        1. Exercise: fundamentals of visualizations
        2. Beyond the default behavior
        3. Exercise: overriding defaults
        4. Show Me
      2. Creating dashboards
        1. Exercise: building a dashboard
        2. Exercise: adding interactivity to a dashboard
    2. Connecting Tableau to your data
      1. Exercise: observing metadata differences
    3. Connecting to Tableau Server
      1. Exercise: connecting to Tableau Server
    4. Connecting to saved data sources
      1. Exercise: creating a local data connection
    5. Measure Names and Measure Values
      1. Exercise: Measure Names and Measure Values
      2. Exercise: Measure Names and Measure values shortcuts
        1. Exercise: commentary
    6. Three essential Tableau concepts
      1. Dimensions and measures
        1. Exercise: dimensions and measures
      2. Row level, aggregate level, table level
        1. Exercise: row level, aggregate level, table level
          1. Exercise: commentary
      3. Continuous and discrete
    7. Exporting data to other devices
      1. Exporting data to a mobile phone
    8. Summary
  8. All About Data - Getting Your Data Ready
    1. Understanding Tableau's data handling engine, hyper
    2. The Tableau data handling engine
      1. Changing field attribution
      2. Table calculation
    3. Hyper takeaways
    4. Data mining and knowledge discovery process models
      1. Survey of the process models
    5. CRISP–DM
      1. CRISP–DM Phases
        1. Phase I: business understanding
        2. Phase II: data understanding
        3. Phase III: data preparation
        4. Phase IV: modeling
        5. Phase V: evaluation
        6. Phase VI: deployment
    6. Focus on data preparation
    7. Surveying data
      1. Exercise: surveying data
      2. Exercise: extrapolating data
      3. Exercise: commentary
    8. Cleaning the data
      1. Exercise: cleaning the data
      2. Exercise: commentary
      3. Exercise: extracting data
      4. Exercise: commentary
    9. Summary
  9. Tableau Prep
    1. Connecting to data
      1. Exercise: connecting data to Tableau Prep
    2. The Tableau Prep GUI
      1. Exercise: getting to know Tableau Prep
    3. Prepping data
      1. Cleaning data
        1. Exercise: cleaning data
      2. Unions and joins
        1. Exercise: unions and joins
      3. Introduction to aggregating
        1. Exercise: aggregating
      4. Pivoting
        1. Exercise: pivoting
    4. Exporting data
    5. Summary
  10. All About Data - Joins, Blends, and Data Structures
    1. Introduction to joins
    2. Introduction to complex joins
    3. Exercise: observing join culling
      1. Exercise: steps
      2. Exercise: commentary
    4. Introduction to join calculations
    5. Introduction to spatial joins
    6. Introduction to unions
      1. Understanding union
    7. Understanding data blending
    8. Order of operations
      1. Exercise: a data blend vs a left join
      2. Exercise: steps
      3. Understanding the join
      4. Understanding the data blend
    9. No dimensions from a secondary source
      1. Exercise: adding secondary dimensions
    10. Introduction to scaffolding
      1. Exercise: enhanced forecasting through scaffolding
    11. Introduction to data structures
    12. Exercise: adjusting the data structure for different questions
      1. Exercise steps: part I
      2. Exercise steps: part II
    13. Summary
  11. All About Data - Data Densification, Cubes, and Big Data
    1. Introduction to data densification
    2. Domain completion
    3. Deployment of domain completion
      1. Exercise: activating domain completion in a crosstab part I
      2. Exercise: activating domain completion in a crosstab part II
      3. Exercise: activating domain completion through view types
    4. Usefulness of domain completion
      1. Exercise: labelling nulls
      2. Problems of domain completion
        1. Exercise: unwanted domain completion
    5. Domain padding
      1. Deploying domain padding through Show Empty Rows/Columns
        1. Exercise: activating domain padding through Show Empty Rows/Columns
      2. Usefulness of domain padding
        1. Exercise: domain padding – filling date gaps
      3. Problematic domain padding
        1. Exercise: from a domain-padded visualization to a crosstab
    6. Working with cubes
      1. Data blending for continuous months
        1. Exercise: data blending for continuous months
      2. Data blending for hierarchies, aliasing, and grouping
        1. Exercise: demonstrating data blending for hierarchies, aliasing, and grouping
    7. The deprecation of cubes
    8. Tableau and big data
    9. Addressing Excel's row limitation
      1. Exercise: Excel's row limitation
    10. Massively parallel processing
    11. Building a visualization with Google BigQuery
      1. Exercise: building a visualization with Google BigQuery
    12. Summary
  12. Table Calculations
    1. A definition and two questions
    2. Introduction to functions
      1. Directional and non-directional
    3. Directional and non-directional table calculations
      1. Exercises: exploring each unique table calculation function
        1. Lookup and Total
        2. Previous Value
        3. Running
        4. Window
        5. First and Last
        6. Index
        7. Rank
        8. Size
    4. Application of functions
      1. Building a playground
      2. Partitioning and addressing with one dimension
      3. Partitioning and addressing with two dimensions
      4. Partitioning and addressing with three dimensions
    5. Summary
  13. Level of Detail Calculations
    1. Building playgrounds
    2. Playground I: FIXED and EXCLUDE
      1. Exercise: exploring Fixed and Exclude and setting up the workbook
        1. Inspecting the worksheet and initial setup
      2. Understanding FIXED
      3. Understanding EXCLUDE
      4. Understanding order of filtering
      5. Exercise: commentary
    3. Playground II: INCLUDE
      1. Inspecting the worksheet and initial setup
      2. Exercise steps: exploring INCLUDE
    4. Practical application
    5. Exercise: practical FIXED
      1. Exercise steps: practical FIXED – the problem
      2. Exercise steps: practical FIXED – table calc solution
      3. Exercise steps: practical FIXED – LOD solution
      4. Exercise: commentary
    6. Exercise: practical INCLUDE
      1. Exercise steps part I – solving using an LOD calculation
      2. Exercise steps part II – solving without an LOD calculation
      3. Exercise: commentary
    7. Exercise: practical EXCLUDE
      1. Exercise steps part I: solving using an LOD calculation
      2. Exercise steps part II: solving using blending
      3. Exercise: commentary
    8. Summary
  14. Section 2: Advanced Calculations, Mapping, Visualizations
  15. Beyond the Basic Chart Types
    1. Improving popular visualizations
      1. Bullet graphs
      2. Exercise steps for the bullet graph: the basics
      3. Exercise steps for bullet graph: beyond the basics
      4. Making useful pies and donuts
        1. Exercise: pies and donuts on maps
          1. Exercise: steps for pies and donuts
      5. Exercise: steps for pies and donuts – beyond the basics
      6. Pareto charts
        1. Exercise: steps for a Pareto chart – the basics
        2. Exercise: steps for a Pareto chart – beyond the basics
    2. Custom background images
      1. Exercise: creating a grid
        1. Exercise: steps for creating a grid
        2. Exercise: steps for using a grid to generate a dataset
        3. Exercise: visualizing a chess game
      2. Exercise: creating polygons on a background image
        1. Exercise: steps for creating polygons on a background image
    3. Tableau extensions
      1. Show me More
        1. Extensions API exercise
    4. Summary
  16. Mapping
    1. Extending Tableau's mapping capabilities without leaving Tableau
      1. Exercise: displaying routes and calculating distances
    2. Extending Tableau mapping with other technology
    3. Exercise: connecting to a WMS server
    4. Exploring the TMS file
      1. The TMS file structure
      2. Accessing popular map servers
        1. ArcGIS
        2. Stamen
    5. Exploring Mapbox
      1. Exercise: Mapbox Classic
      2. Exercise: Mapbox GL
    6. Accessing different maps with a dashboard
      1. Exercise: swapping maps
    7. Creating custom polygons
      1. Exercise: Drawing a square around Null Island
        1. Exercise: steps
    8. Converting shape files for Tableau
    9. Exercise: polygons for Texas
      1. Exercise: steps
    10. Heatmaps
      1. Example
    11. Summary
  17. Tableau for Presentations
    1. Getting the best images out of Tableau
      1. A brief survey of screen capture tools
      2. Tableau's native export capabilities
        1. The five export types
    2. From Tableau to PowerPoint
      1. Exercise: creating a template
      2. Exercise: creating two dashboards
      3. Exercise: creating a PowerPoint presentation
      4. Exercise: automating a weekly PowerPoint presentation
    3. Embedding Tableau in PowerPoint
      1. Exercise: creating an interactive PowerPoint presentation
    4. Animating Tableau
      1. Exercise: creating an animation with Tableau
      2. Exercise: using an animation to export many images
      3. Exercise: using an animation in Tableau to create an animation in PowerPoint
    5. Story points and dashboards for Presentations
      1. Presentation resources
      2. Exercise: using Tableau dashboards to create a PowerPoint-like presentation
    6. Summary
  18. Visualization Best Practices and Dashboard Design
    1. Visualization design theory
    2. Formatting rules
      1. Rule: keep the font choice simple
      2. Rule: using lines in order of visibility
      3. Rule: band in groups of three to five
        1. Exercise: banding
    3. Color rules
      1. Rule: keep colors simple and limited
      2. Rule: respect the psychological implications of colors
      3. Rule: be colorblind friendly
      4. Rule: use pure colors sparingly
        1. Exercise: using pure colors
      5. Rule: color variations over symbol variation
    4. Visualization type rules
      1. Rule: keep shapes simple
        1. Exercise: shapes
      2. Rule: use pie charts sparingly
    5. Compromises
      1. Making the dashboard simple and dashboard robust
      2. Presenting dense information and sparse Information
      3. Telling a story
      4. Documenting
        1. Exercise: tooltips for extensive help
    6. Keeping visualizations simple
    7. Dashboard design
    8. Dashboard layout
      1. The golden rectangle layout
      2. The quad layout
      3. The small multiple layout
    9. Sheet selection
      1. Exercise: sheet swapping pie charts and treemaps
      2. Exercise: collapsible menu
    10. Summary
  19. Advanced Analytics
    1. Self-service Analytics
    2. Use case – Self-service Analytics
    3. Use case – Geo-spatial Analytics
    4. Summary
  20. Improving Performance
    1. Understanding the performance-recording dashboard
    2. Exercise: exploring performance recording in Tableau desktop
    3. Performance-recording dashboard events
    4. Behind the scenes of the performance- recording dashboard
    5. Hardware and on-the-fly techniques
    6. Hardware considerations
    7. On-the-fly-techniques
      1. Exercise: pause/resume auto-updates
      2. Exercise: run update
      3. Exercise: small extracts
    8. Single Data Source > Joining > Blending
    9. Three ways Tableau connects to data
    10. Using referential integrity when joining
      1. Exercise: referential integrity
    11. Advantages of blending
      1. Exercise: necessary blending
    12. Efficiently working with data sources
    13. Tuning data sources
      1. Primary and foreign keys
      2. NOT NULL
      3. Introduction to Index
      4. Indexing
    14. Working efficiently with large data sources
    15. Intelligent extracts
    16. Understanding the Tableau data extract
    17. Constructing an extract for optimal performance
    18. Exercise: summary aggregates for improved performance
    19. Optimizing extracts
    20. Exercise: materialized calculations
      1. Parameters
    21. Using filters wisely
    22. Extract filter performance
    23. Data source filter performance
    24. Context filters
    25. Dimension and measure filters
    26. Table-calculation filters
      1. Exercise: late filter
      2. Using actions instead of filters
    27. Efficient calculations
    28. Boolean/Numbers > Date > String
      1. Exercise: an efficient and an inefficient way to determine N figure salary
      2. Exercise: date vs integer
      3. Level-of-detail calculation or table calculations
    29. Additional performance considerations
    30. Avoid overcrowding a dashboard
    31. Fixing dashboard sizing
    32. Setting expectations
    33. Summary
  21. Section 3: Connecting Tableau to R, Python, and Matlab
  22. Interacting with Tableau Server
    1. Tableau file types
    2. Tableau data source
    3. Tableau packaged data source
      1. Exercise: publishing a data source to Tableau Server
    4. Tableau workbook
    5. Tableau packaged workbook
    6. Other file types
    7. Tableau Server architecture
    8. Tableau Server architecture approaches to avoid
      1. Tableau Server architecture: TWB-centric
      2. Tableau Server architecture: TWBX-centric
    9. Tableau Server architecture approaches to adopt
      1. Tableau Server architecture: TDS-centric
      2. Tableau Server architecture: TDSX-centric
    10. Tableau Server revision history
    11. Tableau Server web-authoring environment
    12. Basic web-authoring instructions
      1. Exercise: editing an existing workbook on Tableau Server
      2. Exercise: creating a new workbook on Tableau Server
    13. Capabilities and limitations of web-authoring
      1. Exercise: the Tableau Server web-authoring environment
    14. Comparing Tableau Desktop and web-authoring
    15. User filters
      1. Exercise: deploying a view-level user filter
    16. Performance-recording dashboard
    17. Exercise: exploring Performance Recording on Tableau Server
    18. More Tableau Server settings
      1. Alerting
      2. Subscribing
      3. Creating custom views
      4. Commenting
      5. Certified Data Source
      6. Tableau Service Manager
    19. Summary
  23. Programming Tool Integration
    1. The architecture
    2. R installation and integration
    3. Installation
      1. Installing R
      2. Integration: starting Rserve, connecting to Tableau, and installing RStudio
    4. Using R functions
      1. Exercise: reproducing native Tableau functionality in R
    5. Introduction to correlations
      1. Exercise: correlations
    6. Introduction to regression analysis
      1. Exercise: regression analysis
    7. Introduction to clustering
      1. Exercise: clustering
    8. Introduction to quantiles
      1. Exercise: quantiles
    9. Troubleshooting in Tableau and R
    10. Examples of troubleshooting in Tableau and R
    11. R scripts and Tableau table calculations
      1. Performance challenges
    12. Python installation and integration
      1. Installation
        1. Installing Python
        2. Integrating Python
    13. Using Python functions
      1. Random and random normal
        1. Exercise: random number
        2. Exercise: random normal
    14. Introduction to sentiment analysis
      1. Exercise: sentiment analysis
    15. MATLAB installation and integration
      1. Installing MATLAB
      2. Integrating MATLAB
      3. Functions of MATLAB
    16. Summary
  24. Other Books You May Enjoy
    1. Leave a review - let other readers know what you think

Product information

  • Title: Mastering Tableau 2019.1 - Second Edition
  • Author(s): Marleen Meier, David Baldwin
  • Release date: February 2019
  • Publisher(s): Packt Publishing
  • ISBN: 9781789533880