I don’t typically write “tool-specific” blog posts. However,
tomorrow I’m presenting at a local Tableau User Group Meeting so I figured I’d
kill 2 birds with 1 stone. If you are not
a Tableau user, hopefully you can find some value in the concepts.
Part of my presentation pertains to optimizing your Tableau
workbooks. The following 10 suggestions are some of my favorites for reducing
workbook size and enhancing the overall performance. Most of these take only a
few seconds to complete and will pay huge dividends.
Every little bit counts!
Please feel free to add your own suggestions in the
comments! I know there are many more Jedi tricks. (& if you know of a way
to do both #4 AND #5 on the same workbook…do tell!)
- Use Extracts when Possible
- Tableau’s Columnar Data Engine is the way to go if you don’t require real-time data
- Optimize Extracts
- Adds your calculated fields to your extract instead of calculating on your desktop
- Filter Data at Data Source Level
- If you have 10 years of data and you’re only reporting the last 5, filter out what you don’t need before you extract.
- Aggregate for Visible Dimensions (& “Roll Dates To”)
- Aggregates your data based on your visualizations (i.e. you have data to Engineer level but we only need to report at Director Level)
- When using dates, specify how far down date hierarchy to view.
- No need to aggregate to the minute or second if you need to display at a weekly view
- Incremental Extracts
- Appends only new data rather than regenerating all data
- Hide All Unused Fields
- Best used when ready for production
- Use Actions instead of quick filters
- Actions Filter the Visualization rather querying your data source
- If you must use filters, use context filters
- Context Filters create a temp table with the results of your filter so that all subsequent filters query only the reduced result set
- String Calculations perform worse than Numeric Calculations.
- Parameters are a great place to leverage this advice
- Do not attempt to Boil the Ocean
- Use workbook case specific datasets rather than 1-size-fits-all solutions, this is not like building a Universe in BO if you’ve worked with that tool.
Cheers,
Kevin Taylor
