Tableau 10 for Data Scientists (2017)

Tableau was made for data science. Learn how to format and filter messy data, use Tableau for data analysis, and visualize data with maps and dashboards.

Introduction

• Welcome
• What you should know
• Exercise files
• Learning supports

1. Green and Blue Pills

• Discrete versus continuous
• Rows and columns
• Filters
• Colors
• Dates
• Pills: Challenge
• Pills: Solution

2. Connect and Extract Data

• Connect to data
• How to create a data extract
• Filter extract
• Extract: Challenge
• Extract: Solution

3. Transform Data

• Clean and prep your data
• Split fields
• Pivoting the data
• Merge data using unions
• Cross database joins
• Join transformations
• Join: Challenge
• Join: Solution

4. Analytics

• Colors to highlight data
• Visual highlighter
• The Analytics pane
• Cross-database filtering
• Analytics: Challenge
• Analytics: Solution

5. Map Your Data

• When to map your data
• Create new maps using MapBox
• Create custom territories
• Mapping: Challenge
• Mapping: Solution

6. Parameters

• Create calculations based on a parameter
• Create dynamic reference lines
• Dynamic dimension and measure selector
• Dynamic sheet selection using parameters
• Top N analysis
• Parameters: Challenge
• Parameters: Solution

7. Dashboard Design

• Dashboard layout tips
• Layout containers
• Filter actions
• Highlight actions
• URL actions
• Formats
• Tooltips
• Device-specific dashboards
• Dashboard: Challenge
• Dashboard: Solution

8. Useful Calculations

• Convert strings to dates
• Calculate time durations
• Create an initial filter from a surname

9. Tableau 10.2 Updates

• Incorporate custom geospatial data into your viz
• Convert string to dates with automatic dateparse
• Create custom joins through calculations
• Export transformed data to CSV
• Display different color legends per measure
• Change the format of fonts and lines across a workbook

Conclusion

• Next steps