BI Validator for Tableau has enabled us to effectively perform: automated regression testing to speed our DB migrations from Netezza to Teradata, automated regression texting for newly developed tableau content, and performance/stress testing of Tableau content against various DB platforms. This client/server toolset is easy to install, configure, and upgrade as we have performed multiple upgrades since originally purchasing it. UI is clean and easy to navigate.

While we've been customers of standalone Datagaps' ETL Validator (ETL V) product for a little over seven years, we recently migrated from ETL V to the DataOps suite (with ETL V & Data Quality) - to take advantage of the more advanced Apache Spark-based platform, inbuilt Python scripting ability as well as extensibility. While there were certainly challenges during migration (as you'd expect with underlying architectural changes), we have had superlative support all through this process. The web-based interface is fairly easy to use - even for business users to define data rules within the application. Scheduling (of Pipelines, DQ Rules, Data Sources, etc.,) and Email alerts are other things we make use of daily. The Data Quality (DQ) module is helping us challenge/address the age-old moniker of garbage in/garbage out in the Data Engineering space with its Data Observability, DQ Score, and other metrics. Look forward to sharing these KPIs and metrics more broadly in our organization.

I have used it for Tableau report data validation against database. It is doing job efficiently. It is very easy to learn and implement. You name the datasource, Datagaps has support to it. It gives flexibility to install app onprem as well as cloud. Customer support is also good. Though I have not done any integration, but it says it can be integrated to your pipelines easily. I would recommend to use it atleast once for BiTest Automation.