The Tableau Performance Checklist: Local Computations – Table Calculations

Data

The Tableau Performance Checklist: Local Computations – Table Calculations

by Anthony Ball

The Tableau Performance Checklist series is designed to help you streamline your dashboard performance and Tableau Server configuration. Each post expands upon one item listed in the master Tableau Performance Checklist.

Here’s the second item under Local Computations:

“Table calculations are powerful, but they can be slow. They are dependent on the local computation engine and can require substantial memory.”

Let’s get started.

Table Calculations

Table calculations are computations that use the values in the entire table and can restructure them for different views and fields. There are two types of fields when it comes to table calculations: partitioning and addressing. Partitioning fields group your data into different buckets. Examples include segmenting sales data by region, product category or by employee. Each of these partitions is then acted upon by the calculations.

Addressing fields determine the direction that your calculation will take. A common addressing field would be date. Using any of the examples above, we could group sales by date or category or employee (partition fields) and then display them in a year-after-year (addressing field), stacked bar chart.

Table calculations are often used to create a common baseline for events that start on different dates, weighted averages, percent of total and more. My colleague Thomas McCullough actually has a great blog post on some essential table calculations that every Tableau user should be familiar with.

Percent of Total Table Calc

Above: A Percent of Total table calc broken down.

Use with Caution

The potential problem with table calculations is that they use the local computation engine. Tableau’s Data Engine is a breakthrough in powering the ad hoc analysis and drag-and-drop features of Tableau Desktop. It is quite powerful, but visualizations that rely quite heavily on table calculations to tell their story can create a performance lag. The more complex the dashboard and the underlying data, the more opportunity for you to improve your visualizations’ performance.

The best thing you can do is to alleviate the workload in Tableau Desktop by preparing the data as much as you can before it is used in the table. This is a common theme throughout the Tableau Performance Checklist. As a data analytics tool, Tableau gives you an incredible amount of power and flexibility in what you create. The big caveat is that if you’re using a substantial amount of data with thousands of users, you’re going to slow down Tableau Server.

You CAN do it, but there are better ways to optimize for performance. And the best way is to do the extra work in your database so that the data is prepared and ready before it hits Tableau Desktop. 

Mastering Best Practices

If you’re interested in becoming a Tableau Server guru, then learning these performance best practices is essential. Check back frequently as we add new posts and dive deeper into each point in the Tableau Performance Checklist.

Another great way to identify best practices is to leverage the insights offered by our Performance Analyzer, part of Workbook Tools for Tableau. It will examine all of your workbooks, worksheets, dashboards and data sources against a list of best practices to ensure that you’re using all the tips and tricks to guarantee your visualizations are moving at light speed.

As always, feel free to get in touch with us if you have any questions regarding performance or anything Tableau related! We’d be happy to help.

Contact Us!

Want More The Tableau Performance Checklist

  1. The Tableau Performance Checklist
  2. The Tableau Performance Checklist: Data – Keep Analysis Simple
  3. The Tableau Performance Checklist: Data – Bring in Only Needed Data
  4. The Tableau Performance Checklist: Data – Use ‘Describe’ to Explore
  5. The Tableau Performance Checklist: Data – Remove Unused Columns from Extracts
  6. The Tableau Performance Checklist: Data – Use One TDS File
  7. The Tableau Performance Checklist: Data – Use Extracts
  8. The Tableau Performance Checklist: Filtering – Minimize Quick Filters
  9. The Tableau Performance Checklist: Filtering – Avoid ‘Only Relevant Values’ in Quick Filters
  10. The Tableau Performance Checklist: Filtering – Avoid High-Cardinality Quick Filters
  11. The Tableau Performance Checklist: Filtering – Avoid Quick Filters That Drive Context Filters
  12. The Tableau Performance Checklist: Filtering – Keep Range Quick Filters Simple
  13. The Tableau Performance Checklist: Filtering – Use Dashboard Filter Actions
  14. The Tableau Performance Checklist: Filtering – Don’t Be Lazy with User Filters
  15. The Tableau Performance Checklist: Custom SQL – Limit in Live Connections
  16. The Tableau Performance Checklist: Custom SQL – Avoid Parameters
  17. The Tableau Performance Checklist: Custom SQL – Watch for Useless Clauses
  18. The Tableau Performance Checklist: Calculations – Use Calculated Fields Carefully
  19. The Tableau Performance Checklist: Calculations – Limit Blended Calculations
  20. The Tableau Performance Checklist: Calculations – Avoid Row-Level Calculations Involving Parameters
  21. The Tableau Performance Checklist: Rendering – Avoid High Mark Counts
  22. The Tableau Performance Checklist: Rendering – Limit Text Tables With Lots of Marks
  23. The Tableau Performance Checklist: Rendering – Minimize Image & Shape File Sizes
  24. The Tableau Performance Checklist: Rendering – Use Transparent Background PNGs
  25. The Tableau Performance Checklist: Local Computations – Server Performance
  26. The Tableau Performance Checklist: Local Computations – Table Calculations
  27. The Tableau Performance Checklist: Dashboard Layout – Limit Number of Worksheets
  28. The Tableau Performance Checklist: Dashboard Layout – Fix Dashboard Size

More About the Author

Anthony Ball

Analytics Consultant
The Tableau Performance Checklist: Local Computations – Table Calculations Here’s the second item under Local Computations: “Table calculations are powerful, but they can be slow. They are dependent on ...
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