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Tableau Jedi

Classroom Training for Advanced Users. Tableau Jedi. PRESENTED BY. Tableau Staff. Base Knowledge. How Tableau Works How to use Tableau How to create advanced visualizations in Tableau How to create and use the following functions: Table Calculations, Parameters, Data Blending.

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Tableau Jedi

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  1. Classroom Training for Advanced Users Tableau Jedi PRESENTED BY Tableau Staff

  2. Base Knowledge How Tableau Works How to use Tableau How to create advanced visualizations in Tableau How to create and use the following functions: Table Calculations, Parameters, Data Blending

  3. Agenda and Schedule 9:00 Welcome, Introduction, & Agenda 9:15 Leveraging Multiple Mark Types 9:45 Table Calculations 10:30 Break 10:45 Table Calculations (cont) 11:15 Parameters 12:00 Lunch 1:00 Quick ways to get your point across 2:00 Break 2:15 Data Blending 3:30Break 3:45 8.0 Preview 4:30 Wrap-Up, Q&A

  4. House Rules Please ask questions Don’t be upset if your question is deferred Please answer questions Don’t interfere with other’s ability to learn Feel free to try it anytime Ask for help if you need it

  5. Jedi Skills • Understand query caching • Force Tableau to behave: • Use multiple mark types liberally • Duplicate fields • Force local calcs: lookup(min[Field],0) • Understand 4 levels of calcs: • Row Level • Field Level (Condition/Top) • View Level (Aggregate) • Higher Level (Table Calcs)

  6. 1. Leveraging Multiple Mark Types LOD Marks Filled Maps with Marks Sales by Region with Total

  7. 1.1 LOD Marks Re-create the view below from Superstore Sales (Training).

  8. 1.2 Filled Maps with Marks Re-create the view below from Sample – Superstore Sales (Excel)

  9. 1.3 Sales by Region with Total Re-create the view below from Sample – Superstore Sales (Excel)

  10. 2. Table Calculations Dynamic Hide Multiple rankings Totals in a header PLUS: Aggregate Bins & Growth rate

  11. 2. Table Calculations Re-create this view from Sample – Superstore Sales (Excel). This view shows the monthly YOY Growth only displaying one year at a time dynamically based on a Parameter.

  12. 2.1 Dynamic Hide Re-create the view below from Sample – Superstore Sales (Excel) (Note that the Filter does not affect the % of Total in the view)

  13. 2.2 Multiple rankings Re-create the view below from Sample – Superstore Sales (Excel)

  14. 2.3 Totals in Titles Re-create the view below from Sample – Superstore Sales (Excel)

  15. 2.4 Totals in a Header Re-create the view below from Sample – Superstore Sales (Excel)

  16. 2.5 Aggregate Bins Re-create this view from Sample – Superstore Sales (Excel). Put our customers into bins based on their total spend. Normal bins work on row level data, but we need them to work on aggregate – sum of sales per customer.

  17. 3. Parameters Controlling partitioning of Table Calculations Parameters & hierarchies (Selectable drill down) Dynamic sorting by multiple rankings

  18. 3.1 Controlling partitioning of Table Calculations Re-create this view from Sample – Superstore Sales (Excel)

  19. 3.2 Parameters & hierarchies (Selectable drill down) Re-create this view from Sample – Coffee Chain (Access)

  20. 3.3 Dynamic sorting by multiple rankings Re-create this view from Sample – Superstore Sales (Excel)

  21. 4. Quick ways to get your point across Spark Lines Legends with Totals Legends with Bullet Charts Reference Lines as totals across disparate sources

  22. 4.1 Spark Lines Re-create this view from Sample – Superstore Sales (Excel)

  23. 4.2 Legends with Totals Re-create this view from Sample – Superstore Sales (Excel)

  24. 4.3 Reference Lines as Totals • Re-create the view below from Sample – Superstore Sales (Excel) & Sample – Coffee Chain (Access) • NOTE: Superstore Sales is the Primary data source, with Coffee Chain being the secondary for this sheet. Sum of Sales is shown from each data set on a shared axis.

  25. 5. Data Blending Creating Primary Group from a secondary source Attributes Open items for any time frame Performance considerations (Blend vs. SQL vs. Calcs?) Best Practices for calculations across disparate sources

  26. 5. Aggregating by a Secondary Dimension • Re-create the view below from Sample – Superstore Sales (Excel) & Sample – Coffee Chain (Access)

  27. 5.2 Open items for any time frame • Re-create the view below from Sample – Superstore Sales (Excel) & a duplicate connection to Sample – Superstore Sales (Excel)

  28. 8.0 Preview… Top N and All Other Compare two sets – customers with repeat purchases and those without Compute Profit when sales in one table and product cost in another

  29. Resources Documentation Knowledge Base Forums Training

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