That’s the Tableau Performance Checklist in its entirety – at least for now. Automatic sizing is less efficient than specifying dashboard size.ĭive Deeper with the Tableau Performance Checklist Series Fix dashboard size relative to end-user consumption.If you have more than four visualizations on a dashboard, strongly reconsider. Limit the number of worksheets on a dashboard.They are dependent on the local computation engine and can require substantial memory. Table calculations are powerful, but they can be slow.Leverage the power of Tableau Server whenever possible by limiting local computations such as groups, hierarchies, reference lines, table calculations and blending. Even if a workbook is published to Tableau Server, local computations still impact performance.Views will render cleaner, and shape files will take up less space. If using custom shapes, use transparent background PNGs instead of JPGs.As a general rule of thumb, keep images under 50kb. Minimize the file size of images or custom shapes where possible.Limit the use of detailed text tables with lots of marks.Avoid row-level calculations involving parameters.Where possible, create a view on the database server. They require sequentially querying multiple data sources and can be time-consuming. Think about the data type as you code the calculation. Number and Boolean > date > string calculations when it comes to performance. Tableau is going to re-sort the data once loaded anyway. Consider building a view in the database or use a multi-table join with filters. Tableau wraps the custom SQL in a subquery that many databases don’t handle well. Avoid parameters in custom SQL in Tableau.Where possible, create a view on the database server to implement your custom SQL and connect Tableau to your view.

Limit custom SQL in live connections as they can be inefficient.

For a detailed view, restrict it to specific users or active directory groups instead of user filters. Consider building a summary view that is a user-agnostic overview using a pre-aggregated extract with underlying data hidden. Security by user filters can impact performance on Tableau Server as the server cannot share connections and query caches if user filters are active. They will cascade as your user interacts, and they perform faster.

Replace quick filters showing “Only Relevant Values” and high count of quick filters with dashboard filter actions.

The more complex the range, the slower the query. These require reloading the context table and should be avoided wherever possible.

Avoid quick filters or actions that drive context filters.

High-cardinality quick filters are slow to load and render.

Avoid high-cardinality quick filters (multi-select or drop-down lists).

Avoid selecting “Only relevant values” for your quick filters.

Use dashboard filter actions where possible. Break hierarchies to only visible dimensions. Roll up data granularity by pre-aggregating or filtering.

Use extracts wherever possible to accelerate performance.

This includes all metadata associated with dimensions, measures, calculated fields, hierarchies, sets, parameters and naming conventions.

Create a published TDS file for your business team to use rather than each analyst creating their own data source.

Remove unused columns (measures/dimensions) in order to minimize extract refresh time or custom SQL query time.

Use “Describe” to explore dimensions in new data sets without having to load them into a viz (keyboard shortcut CTRL+E).

If using a join, minimize the number of joined tables. Consider adding a data source filter or using an extract.

Bring in only the data needed for analysis.

You’ll find those categories with their subsequent best practices in the master list below: Data The Tableau Performance Checklist is divided into seven main categories.

We hope it helps you as much as it’s helped us. So whether your Tableau Server is running slow or Tableau Workbooks seem sluggish, our Tableau Performance Checklist is here to help with performance-saving best practices. The good news is that we learned from these mistakes and took the time to jot down a few ways to maintain peak performance. Of course, excited users inevitably find ways to bog things down. Tableau was designed with usability in mind, apparent in its approachable interface, yet behind that interface lies a powerful collection of components capable of cranking out complex data visualizations at lightning speed. Each post expands upon one item listed in the master Tableau Performance Checklist.Īsk Tableau users what they love most about Tableau, and they’ll likely say it’s the ability to create stunning data visualizations quickly and easily. The Tableau Performance Checklist series is designed to help you streamline your dashboard performance and Tableau Server configuration.

Non sequential checklist