Automating Tableau Reports Validation: The Easy Path to Trusted Insights
Automating Tableau Reports Validation is essential to ensure data accuracy, consistency, and reliability across multiple scenarios. Manual validation can be time-consuming and prone to human error, especially when dealing with complex dashboards and large datasets. By leveraging automation, organizations can streamline the validation process, quickly detect discrepancies, and enhance overall data integrity.
Going ahead, we’ll explore automation of Tableau reports validation and how it is done.
Importance of Automating Tableau Reports Validation
Automating Tableau report validation provides several benefits, ensuring accuracy, efficiency, and reliability in BI reporting.
- Automating the reports validation reduces the time and effort, which allows analysts to focus on insights rather than troubleshooting the errors.
- Automation prevents data discrepancies and ensures all reports are pulling in consistent data.
- Many organizations deal with high volumes of reports and dashboards. It is difficult to manually validate each report. Automating the reports validation becomes critical to maintain efficiency.
- Organizations update their Tableau dashboards very frequently, sometimes daily. On automating the reports validation process, a direct comparison is made between the previous and current data to detect changes or discrepancies. This ensures metrics remain consistent after each data refresh.
- Enabling Automation of Tableau Report Validation with DataOps Suite BI Validator
BI Validator simplifies BI testing by providing a platform for automated BI report testing. It enables seamless regression, stress, and performance testing, making the process faster and more reliable.
Tableau Reports to Database Validation
Tableau reports to Database data comparison ensures that the records from the source data are reflected accurately in the visuals of Tableau reports.
This validation process extracts data from Tableau report visuals and compares it with SQL Server, Oracle, Snowflake, or other databases. Datagaps DataOps Suite BI Validator streamlines this by pulling report data, applying transformations, and verifying consistency through automated row-by-row and aggregate comparisons (e.g., counts, sums, averages).
The errors detected usually identify missing, duplicate or mismatched records.
Automation ensures these issues are caught early, reducing manual effort and improving trust in reporting.
Tableau Regression
In the DataOps suite, Regression testing is done by comparing the benchmarked version of tableau report with the live version of the report through Tableau Regression component.
The comparison can be done in terms of text where the textual differences are highlighted and in terms of appearance where the component performs pixel to pixel comparison of the reports and the visual differences are highlighted.
This Tableau regression component can be very useful for automating the testing of Tableau reports or Dashboards during in-place upgrades or changes.
Tableau Upgrade
Tableau Upgrade Component in BI validator helps in automated report testing by comparing the same or different reports of same or different Tableau sources.
There can be multiple versions of the same Tableau report, especially across different environments. This component is useful for validating these reports. For example, a report may differ between the production and testing environments.
The comparison is done in the same manner as regression testing where the differences between the reports can be pointed out both in terms of text as well as appearance.
Generate BI DataFlows
Generate BI DataFlows is a handy and convenient feature provided by Datagaps DataOps suite to generate multiple dataflows at once for Business Intelligence components like Tableau.
Generate BI DataFlows feature is beneficial in migration scenarios as it enables efficient data comparison between the original and migrated platforms and supports the validations like BI source, Regression and Upgrade.
By generating multiple dataflows based on selected reports, users can quickly detect discrepancies or inconsistencies that may arise during the migration process, ensuring data integrity and accuracy while minimizing potential errors. Furthermore, when dealing with a large volume of reports, this feature speeds up the validation process, minimizes manual effort, and improves overall efficiency in detecting and resolving inconsistencies.
Here’s how the BI Generate Dataflow wizard looks like:
As seen from the image, the wizard starts by generating the Dataflow details. The connection details like the engine, validation type, Source-Data Source and Target-Data Source are to be provided by users.
Let’s take a closer look at the steps involved in “Generate BI Dataflows”
Reports
The Reports section prompts users to select pages from the required reports in the validation process. For Data Compare Validation and Upgrade Validation, both source and target pages will be required. For other cases, only the source page will be needed.
The “Edit Target” wizard allows for manual addition of pages from the target report, providing flexibility and control over the validation scope.
Here is a sample screenshot of the extraction of source and target pages from the source and target report respectively
Visual Mapping and Column Mapping (only in Data Compare Validation)
The “Visual Mapping” section allows users to load and compare source and target pages and then establish connections between corresponding tables.
It consists of three sections namely Source Page, Target Page, and Mapping.
In the source page and target page, respective Tableau worksheets are loaded and on selecting the worksheets option, users can preview the data.
After loading the source and target pages, in the mapping section, the dataset columns of source and target will be automatically mapped for each mapping.
After Visual Mapping, the “Column Mapping” section displays the columns of the source dataset and target dataset that were selected for the data comparison. It provides a count of the number of dataset columns that are mapped and unmapped in the “Mapped” and “Unmapped” tabs respectively.
Filters (for the rest of the validation types)
The filters section enables users to apply the filters and parameters on the reports to help in validating them. These filters can either be applied and selected directly through reports or they can be parameterized as well.
Options
Options section varies depending on the type of validation selected by the user. Options section is the pre final stage of generating the flows where some of the advanced options and comparison options are prompted to be selected as per the liking of the user to get the results as they like.
Here’s a sample screenshot of options section before generating the dataflows
Generate
Generate section helps to generate multiple dataflows with the selected type of validation depending on the number of selected workbooks for tableau.
The above screenshot indicates that four dataflows are set to be generated on clicking the Generate BI Dataflows button. These dataflows are the same type of validation (Tableau Regression Validation in this case)
Stress Test Plan
To automate the stress testing and performance testing of Tableau Reports, Datagaps DataOps suite BI Validator comes with a component called Stress Test Plan to simulate the number of users actively accessing the reports to analyze how Tableau reports 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.
Stress Test Plan allows users to perform the stress testing for multiple views from multiple workbooks at once enabling the flexibility and automation to check for performance bottlenecks of Tableau reports.
For more information on Stress Test Plan, check out “Tableau Performance Testing”.
Integration with CI/CD tools and Pipelines
Until now, we have seen the dataflows being automatically generated for the Tableau Reports Validation. But if a need arises for a dataflow to be a part of your daily pipeline or you want to run the dataflows based on certain deployments. The application comes with the flexibility to integrate with the CI/CD tools like GITHUB Actions or Jenkins.
BI Validator provides a command line interface and REST API for kicking off test plans. Customers can use this interface to execute tests automatically from the CI/CD tools.
In addition to these features, DataOps Suite comes with other interesting features like application in built pipelines where the set of Tableau BI dataflows can be run automatically in a certain order either in sequence or parallel.
Also, there’s an inbuilt scheduler in the application where the users can schedule the run of these pipelines involving these BI dataflows well in advance. The jobs can be scheduled to run once or repeatedly as well.
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