Observe: a harmless, straightforward chart.
It has none of the chart junk, extra ink, or extraneous detail that oftentimes get in the way of interpretation. It contains two clear lines over time that are distinct from each other. And finally, we can see that these lines are very well-correlated.
Being successful in business intelligence hinges on people’s ability to deduce ‘what’s going on with this data‘ and ‘what do I need to do about it.’ Finding insights may appear simple and mindless to do on the surface, but they can actually turn out to be more complicated and time-consuming if you don’t have one, crucial element: context.
And that’s exactly what’s going on with the chart above. In fact, let’s take another look at the same chart, but this time with context.
Per capita cheese consumption correlates with the number of people who died becoming tangled in their bedsheets. Who knew?! Not related at all, but certainly correlated.
It may appear to just be a silly correlation, but without key context, big problems can arise. Being able to comprehend what this information is and why it’s valuable to you and your enterprise-that’s the kind of position companies can be stuck in within business intelligence.
Providing context for the enterprise with natural language generation.
Natural language generation (NLG) can transform data into written analytics and publish to any format, no matter if your data lives in the cloud, within a spreadsheet, or in a complex dashboard.
By pairing NLG with dashboard visualizations, you can keep your dashboard audience engaged by explaining what they need to know and what they need to do about it in plain language. It’s like having a personal data analyst alongside a dashboard, eliminating the risk of misinterpretation by adding context that is specific to the viewer’s role.
For example, NVIDIA uses Automated Insights’ NLG platform, Wordsmith, and Tableau’s visual analytics to optimize internal reporting. Check out the full customer story
