Tableau Fundamentals

Kursusindhold

Tableau Fundamentals

Tableau Fundamentals

1. Introduction to Tableau

What You Will Learn Tableau Installation First Steps Field Operations and Joins Challenge: Joining Tables and Splitting Columns Exploring the Data Pane Challenge: Identifying Top Performers by Profit Pages, Filters, and Marks Overview Challenge: Finding the Sub-Category with the Lowest Sales

2. Tools in Tableau

Dimensions and Measures Challenge: Comparing Sales and Profit by State Continuous and Discrete Fields Challenge: Identifying the Month with Lowest Sales Dimension Filters Measure Filters Challenge: Finding the Most Profitable Customer in Art Calculated Fields Challenge: Comparing California and New York to Other States Interactive Dashboards with Parameters Challenge: Finding the Sub-Category with the Most Sales Working with Sets Challenge: Analyzing Bookcase Profit Concentration Sets Applications

3. Basic Visualizations

Visualizing Data with Heatmaps Challenge: Identifying Top-Selling Sub-Category by Region Scatter Plots Challenge: Determining the Highest Sales and Profit by State Treemaps Challenge: Analyzing the Least Profitable Sub-Category Combination Charts Challenge: Comparing Sales and Profit Trends for Phones Sparklines

4. More Advanced Visualizations

Bullet Graphs Challenge: Analyzing Profit Changes Between 2016 and 2017 Stacked Area Charts Challenge: Identifying the Region with the Highest Profit Histograms Box Plots

Stacked Area Charts

A stacked area chart in Tableau is an effective visualization for showing changes in data over time while highlighting the contribution of each category to the total value. It is especially useful when analyzing trends and proportions within the overall dataset.

Here the key features of stacked area charts:

Why Stacked Area Charts?

Stacked Area Charts are particularly useful for:

Tracking changes in data over time across multiple categories;
Visualizing the proportions and contributions of individual categories;
Analyzing trends within a dataset while maintaining visibility of the total values.

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Sektion 4. Kapitel 3

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Kursusindhold

Tableau Fundamentals

Tableau Fundamentals

1. Introduction to Tableau

What You Will Learn Tableau Installation First Steps Field Operations and Joins Challenge: Joining Tables and Splitting Columns Exploring the Data Pane Challenge: Identifying Top Performers by Profit Pages, Filters, and Marks Overview Challenge: Finding the Sub-Category with the Lowest Sales

2. Tools in Tableau

Dimensions and Measures Challenge: Comparing Sales and Profit by State Continuous and Discrete Fields Challenge: Identifying the Month with Lowest Sales Dimension Filters Measure Filters Challenge: Finding the Most Profitable Customer in Art Calculated Fields Challenge: Comparing California and New York to Other States Interactive Dashboards with Parameters Challenge: Finding the Sub-Category with the Most Sales Working with Sets Challenge: Analyzing Bookcase Profit Concentration Sets Applications

3. Basic Visualizations

Visualizing Data with Heatmaps Challenge: Identifying Top-Selling Sub-Category by Region Scatter Plots Challenge: Determining the Highest Sales and Profit by State Treemaps Challenge: Analyzing the Least Profitable Sub-Category Combination Charts Challenge: Comparing Sales and Profit Trends for Phones Sparklines

4. More Advanced Visualizations

Bullet Graphs Challenge: Analyzing Profit Changes Between 2016 and 2017 Stacked Area Charts Challenge: Identifying the Region with the Highest Profit Histograms Box Plots

Stacked Area Charts

A stacked area chart in Tableau is an effective visualization for showing changes in data over time while highlighting the contribution of each category to the total value. It is especially useful when analyzing trends and proportions within the overall dataset.

Here the key features of stacked area charts:

Why Stacked Area Charts?

Stacked Area Charts are particularly useful for:

Tracking changes in data over time across multiple categories;
Visualizing the proportions and contributions of individual categories;
Analyzing trends within a dataset while maintaining visibility of the total values.

Var alt klart?

Tak for dine kommentarer!

Sektion 4. Kapitel 3

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