Why Context is Essential in Business Intelligence

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

By giving the data in your dashboards context that is personalized to each user, here are a few ways Wordsmith can optimize your internal reporting, scale your operations, and enable your firm to make better data-driven business decisions.

Make data accessible to everyone

Executives, sales reps, account managers-all different positions with different goals. Your company may collect and use the same internal data, but that doesn’t mean everyone should rely on the same contextual analysis. Wordsmith is able to differentiate derived insights depending on the end user, automatically delivering tailored insights to every person within your organization and making them an expert of their own data.

[LIVE DEMO] Try our demo of role-based reporting

Eliminate the risk of misinterpretation

Place a chart or graph in front of 10 people and you can get 10 different interpretations. And who needs 10 different interpretations of cheese consumption and people becoming tangled in bedsheets? Nobody. Context eliminates the risk of misinterpretation, saving you from wasted time, inefficiencies, and making poor business decisions that can stunt the growth of your company.

Confidently share embedded analytics

No longer will your top analysts have to waste their valuable time explaining what’s actually going on with the data in your dashboard visualizations. By using Wordsmith’s written contextual analysis in tandem with your dashboards, confidently share your embedded analytics externally to customers and partners.

Allow analysts to focus on higher valued work

You are an analyst. You’ve designed and configured the most gorgeous-looking, museum-worthy dashboard visualization in existence, but you keep getting asked to explain it and manually write reports to your manager, your boss, and your boss’ boss-the audacity! Data experts and skilled analysts are often in short supply, so why not augment and scale their expertise? Wordsmith gives your analysts the complete control, flexibility, and power to do just that.

To learn more about natural language generation and how you can start incorporating it into BI platforms like Tableau, MicroStrategy, Qlik, and TIBCO Spotfire, request a demo.