Scroll Top

Lire cet article en Français france-drapeau

Ensuring Tableau Pulse Quality:
The Role of Automated
Data Source Testing with Wiiisdom


Tableau AI—A New Era in Data Analytics With A Focus On Tableau Pulse Quality

Tableau AI has become the word of the town—everyone wants to hear more about it and implement it for their organizations. Tableau has now released 2 AI capabilities; Einstein Copilot and Tableau Pulse to make data analysis accessible to everyone and streamline the consumption of insights at scale.

Tableau Pulse debuted in early 2024 quickly becoming the hot topic amongst the Data Fam with its capability to transform data into easily understandable text, providing users with valuable insights and recommendations. Regardless of your experience with data visualization tools, it makes data accessible to everyone and provides Tableau Cloud users with more personalized and contextualized data, and is the most awaited topic at Tableau Conference 2024. However, it’s yet another thing to govern in your Tableau platform. Would you bet your career on a decision made on AI-generated data without a Tableau Pulse quality assurance strategy in place?


Validate Tableau Pulse Insights with Automated Data Source Testing

In order to leverage Tableau Pulse you first need to create metrics and to create these metrics, you need to curate data sources. The success of Tableau Pulse comes from curating data sources to feed Tableau Pulse to provide business stakeholders reliable insights. This is a great innovation, yet it raises an essential question: how can you be sure that the very foundation of Tableau Pulse is accurate and reliable? Given organizations may have numerous data sources, including both older versions and newer versions, how can they be sure the right one is fueling Tableau Pulse?

At Wiiisdom, we are experts in Analytics Governance and I want to demonstrate the different tests you should be carrying out to validate the published data sources. Wiiisdom allows you to implement a series of tests against the data source to make sure the foundation of Tableau Pulse is accurate, reliable, and trusted:

1. Test for data refresh
Wiiisdom ensures that Tableau Pulse is powered by the most up-to-date information by verifying that it uses data marked with the most recent date, guaranteeing accuracy and relevance in its insights provided.

2. Test for row count
Do you have 0 rows but expecting a million or do you have a billion rows but expecting a few thousand? Wiiisdom tests that there are no missing or too many records in the data source thanks to row count tests.

3. Test for specific column values
If there are specific column values that you want to test in your data source, Wiiisdom can validate their accuracy by running tests on each one automatically. For example, let’s say you have a column that should have 4 values. In Wiiisdom, you can set up a test looking for those 4 values; if one is missing, the test will fail and if there are too many, the test will also fail.


Get AI-generated Insights That You Can Trust

There’s no doubt that Tableau Pulse represents a significant advancement in making data accessible to everyone offering insights and recommendations through Tableau Cloud. However, the reliability of these insights hinge on the accuracy and integrity of the underlying data sources. By implementing automated data source testing for Tableau Pulse using Wiiisdom, you can be confident that the foundation upon which Tableau Pulse operates is reliable, thus reinforcing the trust business stakeholders place in this AI-generated data.

Leave a comment