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Advanced Tableau Desktop

Advanced Tableau Desktop

11hAdvanced2024-09-11

Authors

Maven Analytics

Maven Analytics

Dustin Cabral

Dustin Cabral

Course details

If you’re ready to build expert-level data analysis and visualization skills with Tableau Desktop, you’ve come to the right place. This course is a hands-on and project-based dive deep into several advanced Tableau topics, ranging from data relationships and calculations to predictive analytics and dynamic design techniques.

See how to apply these tools to real-world business intelligence use cases by playing the role of a newly hired analyst for Maven Roasters, a bespoke, small batch coffee roasting company. Your mission? Use advanced analytics and visual design tools to take the company’s BI reports to the next level.

Throughout the course, you’ll come across unique opportunities to put your new skills to the test, like analyzing employee earnings for the Boston Police Department, building forecast models for the World Health Organization, and designing geospatial dashboards to help FEMA identify environmental risks.

Skills covered

TableauTableau SoftwareData VisualizationBusiness AnalyticsData AnalysisData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOne-Off

Concepts

Getting Started

  • 01 - Course structure and outline
  • 02 - Introducing the course project

1. Relationships

  • 03 - Relationships
  • 04 - Logical and physical layers
  • 05 - Relationships vs. joins
  • 06 - Requirements for relationships
  • 07 - Creating relationships
  • 08 - Optimizing performance
  • 09 - Multi-fact relationships
  • 10 - Interface differences (2020.2)
  • 11 - The 8 R's of relationships
  • 12 - Contextual joins - Remain
  • 13 - Contextual joins - Relevant
  • 14 - Contextual joins - Retain
  • 15 - Contextual joins - Recovered
  • 16 - Contextual joins - Represented
  • 17 - Contextual joins - Removed
  • 18 - Smart aggregation
  • 19 - Smart aggregation - Replicate
  • 20 - Smart aggregation - Resolve
  • 21 - Assignment - Relationships
  • 22 - Solution - Relationships

2. Dynamic Design

  • 23 - Dynamic design
  • 24 - Visual appeal
  • 25 - Background templates
  • 26 - KPI shapes
  • 27 - Info icons
  • 28 - Instructions and commentary
  • 29 - Flexibility
  • 30 - Multi-dimensions
  • 31 - Multi-measures
  • 32 - Pro tip - Dynamic formatting
  • 33 - Sheet selectors
  • 34 - Filter menus

3. Parameter and Set Actions

  • 35 - Interactivity
  • 36 - Parameter actions
  • 37 - Parameter actions - Multi-measure
  • 38 - Parameter actions - Index chart
  • 39 - Parameter actions - Year-over-year
  • 40 - Parameter actions - Sheet selector
  • 41 - Parameter actions - Relative dimensional analysis
  • 42 - Set actions
  • 43 - Set actions - Proportional brushing
  • 44 - Set actions - Asymmetric drilldown
  • 45 - Set actions - Color scaling
  • 46 - Pro tip - Viz animations
  • 47 - Pro tip - Viz extensions
  • 48 - Assignment - Dynamic design and actions
  • 49 - Solution - Dynamic design and actions

4. Geospatial Mapping

  • 50 - Geospatial mapping
  • 51 - Geospatial data
  • 52 - The mapping workspace
  • 53 - Geospatial use cases
  • 54 - Standard maps
  • 55 - Spatial functions
  • 56 - Custom territories
  • 57 - Map hierarchies
  • 58 - Geospatial customization
  • 59 - Map layers
  • 60 - Background maps - WMS
  • 61 - Background maps - Mapbox
  • 62 - Background images
  • 63 - Common mapping issues
  • 64 - Assignment - Geospatial mapping
  • 65 - Solution - Geospatial mapping

5. Advanced Calculations

  • 66 - Advanced calculations
  • 67 - Regular expressions
  • 68 - Regular expressions functions
  • 69 - Review - Table calculations
  • 70 - Review - Addressing and partitioning
  • 71 - Position-based table calculations functions
  • 72 - Pro tip - Index top filter
  • 73 - Review - Level of detail expressions
  • 74 - Choosing an LOD type
  • 75 - LOD use case - Benchmarking and time flags
  • 76 - LOD use case - Customer order frequency
  • 77 - LOD use case - Cohort analysis
  • 78 - LOD use case - New customer acquisition
  • 79 - Assignment - Advanced calculations
  • 80 - Solution - Advanced calculations

6. Predictive Analytics

  • 81 - Predictive analytics
  • 82 - Regression models
  • 83 - Trend lines
  • 84 - Forecasting
  • 85 - Control charts
  • 86 - Clustering
  • 87 - R and Python integration
  • 88 - Dashboard extensions
  • 89 - Assignment - Geospatial mapping
  • 90 - Solution - Geospatial mapping

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