book

The Tableau Workshop

Name: The Tableau Workshop
ISBN: 9781800207653

by Sumit Gupta, Sylvester Pinto, Shweta Savale, JC Gillet, Kenneth Michael Cherven

April 2022

Beginner

822 pages

14h 43m

English

Packt Publishing

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The Tableau Workshop
Preface
About the BookAbout the AuthorsWho This Book Is ForAbout the ChaptersConventionsMinimum Hardware RequirementsMinimum Software RequirementsDownloading the Book/Data Sources BundleSetting Up Your EnvironmentInstalling Tableau on Your SystemGet in TouchPlease Leave a Review
1. Introduction: Visual Analytics with Tableau
IntroductionThe Importance of Visual AnalyticsThe Tableau Product SuiteIntroduction to Tableau DesktopExercise 1.01: Connecting to a Data SourceExercise 1.02: Creating a Comparison Chart Using Manual Drag and DropExercise 1.03: Creating a Comparison Chart Using the Automated Show Me Button MethodData Visualization Using Tableau DesktopSaving and Sharing Your WorkExercise 1.04: Saving Your Work as a Static Snapshot-PowerPoint ExportExercise 1.05: Saving Your Work as a Tableau Interactive File–Tableau Packaged WorkbookActivity 1.01: Identifying and Creating the Appropriate Chart to Find Outliers in Your DataSummary
2. Data Preparation: Using Tableau Desktop
IntroductionConnecting to a Data SourceExercise 2.01: Connecting to an Excel FileConnecting to a Server Data SourceVarious Joins in TableauDifferent Types of JoinsExercise 2.02: Creating an Inner Join DatasetExercise 2.03: Creating a Left Join DatasetExercise 2.04: Creating a Right Join DatasetExercise 2.05: Creating a Combined Dataset Using UnionData Transformation in the Data PaneData InterpreterRenaming the Data SourceLive and Extract ConnectionsExercise 2.06: Creating an Extract for DataExtract PropertiesThe Data Storage fieldThe Filters fieldThe Aggregation FieldThe Number of Rows FieldWhich Connection Is Better – Live or Extract?FiltersExercise 2.07: Adding a Region Filter on the Orders TableData Grid OptionsCustom SQLData BlendingExercise 2.08: Creating a Data Blend Using the Orders and People TablesExercise 2.09: Visualizing Data Created from a Data BlendLimitations of Data BlendingActivity 2.01: Identifying the Returned OrdersActivity 2.02: Preparing Data for VisualizationSummary
3. Data Preparation: Using Tableau Prep
IntroductionPrep InterfaceAdding Data in the FlowExercise 3.01: Connecting to an Excel FileExercise 3.02: Connecting with Multiple Data SourcesData Source ProfileExercise 3.03: Data Profile for the Orders_South DatasetData Preparation Using Clean, Groups, and SplitAdditional Clean StepsCleaning Steps at the Column LevelExercise 3.04: Applying a Filter in a Clean StepExercise 3.05: Cleaning a Column in the WorkflowGrouping ValuesExercise 3.06: Grouping Values into a GroupSplitting ValuesExercise 3.07: Splitting ColumnsAggregation, Pivot, Join, and UnionAggregationsExercise 3.08: Identifying High-Value Customers Based on PurchasesPivoting DataExercise 3.09: Using a Pivot for DataJoining and Union of DataExercise 3.10: Joining Two Data SourcesUnionExercise 3.11: Union of TablesScript StepFlow and Data ExportsExercise 3.12: Exporting DataActivity 3.01: Finding the Month with the Highest OrdersActivity 3.02: Data TransformationSummary
4. Data Exploration: Comparison and Composition
IntroductionExploring Comparisons across Dimensional ItemsBar ChartExercise 4.01: Creating Bar ChartsExploring Comparisons over TimeExercise 4.02: Creating Bar Charts for Data over TimeLine ChartsDifference between Discrete Dates and Continuous Dates Exercise 4.03: Creating Line Charts over TimeExploring Comparison across MeasuresExercise 4.04: Creating a Bullet ChartBar-in-Bar ChartsExercise 4.05: Creating a Bar-in-Bar ChartExploring Composition Snapshots – Stacked Bar ChartsExercise 4.06: Creating a Stacked Bar ChartExploring Composition Snapshots – Pie ChartsExercise 4.07: Creating a Pie ChartTreemapsExercise 4.08: Creating Treemaps Exploring Compositions for Trended DataArea ChartsExercise 4.09: Creating an Area ChartActivity 4.01: Visualizing the Growth of Passenger Cars in Singapore Summary
5. Data Exploration: Distributions and Relationships
IntroductionExploring Distribution for a Single MeasureCreating a HistogramExercise 5.01: Creating a HistogramBox and Whisker PlotsExercise 5.02: Creating a Box and Whisker Plot without the Show Me PanelExercise 5.03: Box Plot Using the Show Me PanelRelationship and Distribution with Multiple MeasuresDistribution with Two MeasuresCreating a Scatter PlotExercise 5.04: Creating a Scatter PlotScatter Plots with Trend LinesExercise 5.05: Trend Lines with Scatter PlotsTrend Lines and TypesLinear Trend LinesPolynomial Trend LinesPolynomial Degree of FreedomLogarithmic Trend LinesExponential Trend LinesPower Trend LinesThe Reliability of Trend LinesR-SquaredP-valueAdvanced ChartsQuadrant ChartsReference LinesUnderstanding Reference LinesExercise 5.06: Creating Quadrant ChartsCombination Charts – Dual axis ChartsExercise 5.07: Creating Dual axis ChartsActivity 5.01: Creating Scatter PlotsActivity 5.02: Dual axis Chart with Asynchronous AxesSummary
6. Data Exploration: Exploring Geographical Data
IntroductionImporting Spatial DataData File TypesESRI ShapefilesGeoJSON FilesKML FilesMapInfo Interchange FormatMapInfo TablesTopoJSON FilesDownloading the Data Source from GitHubExercise 6.01: Downloading the Source DataImporting Non-Spatial Geographic Data SourcesExercise 6.02: Importing a Non-Spatial Data SourceData RelationshipsExercise 6.03: Joining Two Data SourcesManaging Location DataAssigning Geographic RolesEditing LocationsBuilding Custom GeographiesCreating a New Geography Using an Existing RoleCreating a New Geography Using GroupsExercise 6.04: Building Custom GeographiesCreating Maps in TableauGeocodingSymbol MapsAdding Data to Symbol MapsColoring a Symbol MapSizing a Symbol MapUsing Shapes in a Symbol MapAdding Map TooltipsNavigating Symbol MapsFiltering Symbol MapsCreating Groups and Sets from Symbol Map DataExercise 6.05: Building a Symbol MapChoropleth (Filled) MapsColoring a Choropleth MapNavigating a Choropleth MapFiltering a Choropleth MapExercise 6.06: Building a Choropleth MapDual-Axis MapsExercise 6.07: Creating a Dual-Axis MapMap EnhancementsSetting Map OptionsUsing Existing LayersAdding Mapbox Background MapsExercise 6.08: Adding Mapbox Background MapsActivity 6.01: Creating a Location Analysis Using Dual Axis and Background MapsSummary
7. Data Analysis: Creating and Using Calculations
IntroductionCreating and Using Ad hoc / Edit in Shelf CalculationsExercise 7.01: Creating an Ad Hoc Calculation to Highlight Loss-Making Sub-CategoriesCreating and Using Different Types of CalculationsCreating and Using Different Types of Calculations: Numeric CalculationsExercise 7.02: Creating a Numeric CalculationCreating and Using Different Types of Calculations: Logic StatementsExercise 7.03: Creating a Logic CalculationCreating and Using Different Types of Calculations: String CalculationsExercise 7.04: Creating a String CalculationCreating and Using Different Types of Calculations: Date CalculationsExercise 7.05: Creating a Date CalculationHandling Null Values while Creating and Using CalculationsCreating Calculations across Data SourcesActivity 7.01: Calculating the Profit MarginActivity 7.02: Calculating the Percentage Achievement with Respect to Budget SalesSummary
8. Data Analysis: Creating and Using Table Calculations
IntroductionQuick Table CalculationsRunning TotalExercise 8.01: Creating a Running Total CalculationDifferenceExercise 8.02: Creating a Difference CalculationPercent of TotalExercise 8.03: Creating a Percent of Total CalculationPercent DifferenceExercise 8.04: Creating a Percent Difference CalculationPercentile and RankExercise 8.05: Creating Percentile and Rank CalculationsMoving AverageExercise 8.06: Creating a Moving Average CalculationTable Calculation Application: Addressing and PartitioningTable (across)Exercise 8.07: Creating a Table (across) CalculationTable (down)Exercise 8.08: Creating a Table (down) CalculationExercise 8.09: Creating Table (across then down) and Table (down then across) CalculationsExercise 8.10: Creating a Pane (across) CalculationExercise 8.11: Pane (down) CalculationExercise 8.12: Creating a Pane-Level CalculationCellCreating, Editing, and Removing Table CalculationsCreating a New Table CalculationExercise 8.13: Creating a Table Calculation Using the Calculation EditorRemoving a Table CalculationActivity 8.01: Managing Hospital Bed AllocationsActivity 8.02: Planning for a Healthy PopulationSummary

9. Data Analysis: Creating and Using Level of Details (LOD) Calculations
IntroductionExercise 9.01: Creating a LOD CalculationTypes of LOD CalculationsFIXEDExercise 9.02: Creating a FIXED LOD CalculationINCLUDEExercise 9.03: Creating an INCLUDE LOD CalculationEXCLUDE Exercise 9.04: Creating an EXCLUDE LOD CalculationTable-Scoped LOD Calculations: Dimensions or Measures?Aggregation and LOD CalculationsLOD Calculation Is Higher than the View LODLOD Calculation Is Finer than the View LODNested LOD CalculationsEffects of Filters on LOD CalculationsActivity 9.01: Identifying the Top-Performing Sales ExecutivesActivity 9.02: Performing a Comparative AnalysisSummary
10. Dashboards and Storyboards
IntroductionThe Who, What, and Why of the DashboardThe Who: AudienceThe What: Begin with the End in MindThe Why: The Need for a Dashboard Designing a DashboardThe Basic LayoutDisplay SizePositioningSpacingColorsSizeTextExercise 10.01: Text Formatting – Workbook versus Worksheet Dashboard ObjectsVertical ObjectsHorizontal ObjectsText ObjectsImage ObjectsWeb Page ObjectsBlank ObjectsNavigation ObjectsExtension ObjectUsing Floating ObjectsExercise 10.02: KPIs and Metrics ViewExercise 10.03: Map and Parameter Worksheet ViewsExercise 10.04: Putting It All Together: DashboardingCreating StoryboardsExercise 10.05: Creating a Simple StoryboardActivity 10.01: Building a Complete DashboardSummary
11. Tableau Interactivity: Part 1
IntroductionGrouping DataExercise 11.01: Creating GroupsHierarchiesExercise 11.02: Creating HierarchiesFilters: The Heart and Soul of TableauData Source and Extract FiltersExercise 11.03: Filtering Data Using Extract/Data Source FiltersFilters Using ViewsExercise 11.04: Creating Filters from the ViewCreating Filters Using the Filters ShelfDimension Filters Using the Filters ShelfExercise 11.05: Dimension Filters Using the Filters ShelfMeasure Filters Using the Filters ShelfExercise 11.06: Measuring Filters Using the Filters ShelfDate Filters Using the Filters ShelfExercise 11.07: Creating Date Filters Using the Filters ShelfQuick FiltersExercise 11.8: Creating Quick FiltersApplying Filters across Multiple Sheets/Multiple Data Sources or an Entire Data SourceContext FiltersExercise 11.09: Creating and Using Context FiltersSetsStatic SetsExercise 11.10: Creating Static SetsDynamic SetsExercise 11.11: Creating Dynamic SetsAdding Members to the SetExercise 11.12: Adding Members to the SetCombined SetsExercise 11.13: How to Create Combined SetsParametersExercise 11.14: Standard ParametersDynamic ParametersExercise 11.15: Dynamic ParametersActivity 11.01: Top N Countries Using Parameters, Sets, and FiltersSummary

Overview

The Tableau Workshop offers a comprehensive, hands-on guide to mastering data visualization with Tableau. Through practical exercises and engaging examples, you will learn how to prepare, analyze, and visualize data to uncover valuable business insights. By completing this book, you will confidently understand the key concepts and tools needed to create impactful data-driven visual stories.

What this Book will help me do

Master the use of Tableau Desktop and Tableau Prep for data visualization tasks.
Gain the ability to prepare and process data for effective analysis.
Learn to choose and utilize the most appropriate chart types for different scenarios.
Develop the skills to create interactive dashboards that engage stakeholders.
Understand how to perform calculations to extract deeper insights from data.

Author(s)

Sumit Gupta, None Pinto, Shweta Savale, JC Gillet None, and None Cherven are experts in the field of data analytics and visualization. With diverse backgrounds in business intelligence and hands-on experience with industry tools like Tableau, they bring valuable insights to this book. Their collaborative effort offers practical, real-world knowledge tailored to help learners excel in Tableau and data visualization. With their passion for making technical concepts accessible, they guide readers step by step through their learning journey.

Who is it for?

This book is ideal for professionals, analysts, or students looking to delve into the world of data visualization with Tableau. Whether you're a complete beginner seeking foundational knowledge, or an intermediate user aiming to refine your skills, this book offers the practical insights you need. It's designed for those who want to master Tableau tools, explore meaningful data insights, and effectively communicate them through engaging dashboards and stories.

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