Tableau 10 for Data Scientists
Offered By: LinkedIn Learning
Course Description
Overview
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.
Syllabus
Introduction
- Welcome
- What you should know
- Exercise files
- Learning supports
- Discrete versus continuous
- Rows and columns
- Filters
- Colors
- Dates
- Pills: Challenge
- Pills: Solution
- Connect to data
- How to create a data extract
- Filter extract
- Extract: Challenge
- Extract: Solution
- Clean and prep your data
- Split fields
- Pivoting the data
- Merge data using unions
- Cross database joins
- Join transformations
- Join: Challenge
- Join: Solution
- Colors to highlight data
- Visual highlighter
- The Analytics pane
- Cross-database filtering
- Analytics: Challenge
- Analytics: Solution
- When to map your data
- Create new maps using MapBox
- Create custom territories
- Mapping: Challenge
- Mapping: Solution
- 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
- Dashboard layout tips
- Layout containers
- Filter actions
- Highlight actions
- URL actions
- Formats
- Tooltips
- Device-specific dashboards
- Dashboard: Challenge
- Dashboard: Solution
- Convert strings to dates
- Calculate time durations
- Create an initial filter from a surname
- 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
- Next steps
Taught by
Matt Francis
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