We here at Tableau are very proud of how easy it is to see and understand data with Tableau. Once you get started, it’s intuitive to dive deeper by adding more and more fields, formulae, and calculations to a simple visualization—until it becomes slower and slower to render. In a world where two-second response times can lose an audience, performance is crucial.
So where do I start?
So how can you make your dashboards run faster? Your first step is to identify the problem spots by running and interpreting your performance recording. The performance recorder is every Tableau speed demon’s ticket to the fast lane. The performance recorder can pinpoint slow worksheets, slow queries, and long render-times on a dashboard. It even shows the query text, allowing you to work with your database team on optimizing at the database level.
Now that you know which views or data connections are slowing you down, below are six tips to make those dashboards more performant. For each tip, we’ve listed the most common causes of performance degradation as well as some quick solutions.
To get in-Depth knowledge on Tableau Dashboard you can enroll for live Tableau Online Training
1. Your data strategy drives performance
Extracts are typically much faster to work with than a live data source, and are especially great for prototyping. The key is to use domain-specific cuts of your data. The Data Engine is not intended to be a replacement for a data warehouse. Rather, it’s meant to be a supplement for fast prototyping and data discovery.
Keep in mind: Extracts are not always the long-term solution. The typical extent of an extract is between 500 million to one billion rows; mileage will vary. When querying against constantly-refreshing data, a live connection often makes more sense when operationalizing the view.
2. Reduce the marks (data points) in your view
When data is highly granular, Tableau must render and precisely place each element. Each mark represents a batch that Tableau must parse. More marks create more batches; drawing 1,000 points on a graph is more difficult than drawing three bars in a chart.
Large crosstabs with a bevy of quick filters can cause increased load times when you try to view all the rows and dimensions on a Tableau view.
Excessive marks (think: data points) on a view also reduce the visual analytics value. Large, slow, manual table scans can cause information overload and make it harder to see and understand your data.
Here’s how you can avoid this trap:
3. Limit your filters by number and type
Filtering in Tableau is extremely powerful and expressive. However, inefficient and excessive filters are one of the most common causes of poorly performing workbooks and dashboards. Note: Showing the filter dialog requires Tableau to load its members and may create extra queries, especially if the filtered dimension is not in the view.
4. Optimize and materialize your calculations
Perform calculations in the database. Wherever possible, especially on production views, perform calculations in the database to reduce overhead in Tableau. Aggregate calculations are great for calculated fields in Tableau. Perform row-level calculations in the database when you can.
Reduce the number of nested calculations. Just like Russian nesting dolls, unpacking a calculation and then building it takes longer for each extra layer.
Reduce the granularity of LOD or table calculations in the view. The more granular the calculation, the longer it takes.
LODs - Look at the number of unique dimension members in the calculation.
Table Calculations - the more marks in the view, the longer it will take to calculate.
Where possible, use MIN or MAX instead of AVG. AVG requires more processing than MIN or MAX. Often rows will be duplicated and display the same result with MIN, MAX, or AVG.
Make groups with calculations. Like include filters, calculated groups load only named members of the domain, whereas Tableau’s group function loads the entire domain.
Use Booleans or numeric calculations instead of string calculations. Computers can process integers and Booleans (t/f) much faster than strings. Boolean>Int>Float>Date>DateTime>String
5. Take advantage of Tableau’s query optimization
6. Clean up your workbooks!
Take your career to new heights of success with a tableau training
#tableau #tableu #dashboard #technology #businessintelligence