What is performance testing in Tableau?
Tableau performance testing is the process of evaluating the speed, efficiency, and responsiveness of the tableau dashboards, reports, worksheets, data connections, and queries to ensure smooth and efficient user experience.
As we progress through the blog, we’ll delve into different aspects of Tableau Performance Testing.
Importance of Tableau Performance Testing
Many organizations depend on Tableau dashboards and reports to make important decisions. When they underperform, it can lead to delays or compromises in the decision-making process.
There may be instances where reports consume significant time and resources, especially when multiple users access them simultaneously. Performance testing helps identify which reports and dashboards are causing these issues within the server infrastructure and can assist in reducing costs.
Tableau Performance Testing ensures data reliability as the filters, calculations and rendering are tested for the reports and pages to verify if they work well under various conditions.
Performance testing of Tableau reports helps organizations embed dashboards that load smoothly and scale effectively, ensuring a positive user experience within business applications.
If a dashboard takes more than few seconds to respond to filter selections or parameter changes, users might abandon it. Well optimized Tableau dashboards, achieved through performance testing increase user confidence and trust in the platform.
Tableau Performance Testing using Datagaps DataOps Suite’s BI Validator
Datagaps DataOps Suite’s BI Validator allows users to do Performance testing on Tableau reports with a component called Stress Test Plan.
Stress Test Plan works by simulating the number of users actively accessing the reports to analyze how Tableau reports optimization and dashboards perform under heavy load. Results of the stress test plan can be used to point out performance issues, optimize data models and queries to ensure the robustness of the Tableau environment to handle heavy usage patterns.
The plan involves running multiple users attempting different activities like viewing reports, refreshing data, interacting with visuals. In this way, stress is simulated in the Tableau environment based on the applied parameters for performance testing. This testing facilitates the iterative optimization of reports, making them more suitable for deployment, as well as ensuring reliability and Tableau scalability.
How does Stress Test Plan achieve Tableau Performance Testing?
- Datagaps DataOps Suite’s BI Validator has a BI DevOps section where users can select the “Stress Test Plan” and click on “Add Stress Test Plan”.
- There, users can select Tableau sources.
- On clicking next, the “Add stress plan” will appear asking the users to select the applicable Tableau Source where the reports are present.
- After saving the stress test plan, the next step is to add a workbook to the Stress Test Plan.
- The “Add Reports” section will prompt users to select the appropriate Site ID and project from the chosen data source, as well as choose views from the available workbooks, as shown below.
- Once selected, the views can be added to the stress test plan.
Important Parameters to perform the Stress Test Plan
“Run Options” within the stress test plan allows users to configure the set of parameters to simulate the execution of Stress Test.
No. of users in parallel: specifies the number of concurrent users that will be simulated to log in to Tableau Environment.
Ramp up time: time period for the specified no. of users to log in to environment.
Think time: waiting time period in seconds for a user when navigating from one page to another page.
Time out: maximum allowable time in seconds for a page to load before a timeout is triggered.
Run time: Total duration in seconds for which the stress test plan will run.
SLA: Service Level Agreement, which defines the maximum acceptable response time for loading the report during the stress test. It alerts the user that the page load time has exceeded the expected threshold (in seconds).
Screenshot sample %: The percentage of snapshots captured from the report during the execution of the stress test plan.
Refresh time: sets the interval at which the BI reports will be refreshed during the stress test.
Users List: If specific users are listed, system will simulate the test by logging them into the environment concurrently allowing for more diverse and realistic simulation by mimicking multiple unique users accessing the system simultaneously. If no users are specified in the “Users List”, the system will log in the same user repeatedly, in parallel, based on the specified number of users.
Filter Dataset
The Filter Dataset option allows users to perform testing for multiple reports with different filter combinations. These filters can be parameterized for the reports as filter datasets. Each dataset represents a specific set of filter combinations, allowing the user to select different filter criteria for the same report.
A sample screenshot of the dataset preview is shown below where a dataset has 12 filter combinations for a report.
Run Results
On successful execution of the Stress Test Plan, status will be updated as ‘completed’.
A sample screenshot of the ‘Run’ result is shown below.
We can see that the run results will show the important metrics like Average Run Time, Average Filter Applied time, Max Run Time, Max Filter Applied time, Run count indicating how many requests have been made and SLA Failures if there are any.
On clicking a particular page, respective metrics will be displayed along with the steps involved in testing that page.
The two graphs from the screenshot are:
- User Count Vs Number of Requests per sec (left side)
- Average Run Time in seconds Vs Number of Requests (right side)
Run History
Run History section provides the historical record of previous runs. This allows users to review the run results and important information such as execution times, errors and other metrics.
On opening a stress test plan and clicking on the run history icon, run history will be displayed with selection criteria of run, run date between, run by, filter and clear all.
Boost Your Tableau Performance with BI Validator
Overcome performance issues and ensure smooth, scalable Tableau reports with Datagaps BI Validator.
