What if you could take a dashboard, publish it, and then send it out to everyone in your entire organization accompanied with a written summary? A written summary, we might add, that is completely automated, updates in real-time, and provides contextual analysis on the data behind your dashboards.It sounds good, right? It sounds optimal. Efficient. Scaleable. Even magical. You name it.It’s all possible (and a whole lot more!) with our NLG platform, Wordsmith, and Tableau’s new Extensions API.
Automated Insights (Ai) Featured at Tableau Conference Keynote
It’s fair to say that Tableau Conference 2017 was pretty epic for us here at Ai. In front of 15K attendees, and thousands more around the world, Tableau unveiled a new integration allowing users the ability to integrate Automated Insights’ NLG directly within their dashboards, scaling expertise and adding context in real-time.
Charting a Course for the Future of BI
“Using the boundary-breaking power of the Extensions API along with the magic of Ai, our partner Automated Insights is automatically populating this dashboard with that written summary,” said Ben Lower, Product Manager at Tableau during his keynote address.
With this first-ever integration of its kind, bringing real-time natural language analysis directly within Tableau dashboards, Automated Insights is enabling Tableau users with the ability to alleviate misinterpretation, reduce time to insight, and to scale data expertise on an unprecedented scale.
Ai is enabling companies such as NVIDIA to expand the reach of their best data analysts across their organization. The integration allows NVIDIA to get a fully contextual explanation of their entire dashboard; explaining how the individual charts that comprise the dashboard are related and even surfacing insights that may not be visualized.
We were ecstatic to get to partner with such an innovative company and a leader within the Artificial Intelligence space. NVIDIA’s marketing team relies on Tableau dashboards, so using NLG, NVIDIA wanted to accomplish three things:
1. Streamline reporting from multiple sources
2. Turn data into actionable insights
3. Make decisions faster
To learn more about how Ai helped NVIDIA accomplish these three things, head over to our NVIDIA Case Study.