From What to Why: How Contextual Insights Elevate BI

TL;DR

Traditional dashboards often show what happened but not why, causing a decision-making gap. The solution lies in adding contextual insights, made possible using tools such as gen AI and natural language query (NLQ), which empower business users to get plain-English explanations and ask their own questions, leading to greater confidence, agility, and business impact. 

Book a demo and try Yellowfin AI-assisted contextual insights for yourself.

Tired of your business intelligence (BI) platform telling you what happened, without a clue as to why? 

That's the data gap typical of a traditional BI solution. It leaves your users with static dashboards that are all show, no tell. 

We’re going to fix that. 

Let’s explore how Yellowfin is weaving contextual insights and AI-powered analytics technologies like natural language query (NLQ) into your app to help transform uncertainty into action, and empower your users to get the full story, not just the stats.

Why is only knowing the 'what' in data not enough?

That dashboard you bought or built, or the one you sold, might be pretty to look at. But imagine your customer or product manager logging in to see a key metric in a terrifying shade of red. 

The business intelligence dashboard proudly tells them what happened: user engagement dropped 15% this week. However, traditionally, this sort of dashboard is completely silent on the why. 

Was it a recent feature update? A backend issue? A competitor's new campaign?

Now, the scavenger hunt begins. Your user now has to manually dig for the answer, and some can. However, if they don’t have data expertise or time, they will likely have to ping your data or IT team to get an answer, and hope someone has time to run a custom query. The hours tick by. 

Ultimately, the traditional reporting process is a drag on momentum, a delay in crucial decisions, and a slow erosion of trust in the BI solution you just invested in, meant to provide answers.

Enter the "why": What is the power of contextual insights?

This is where the "why" enters the chat.

Picture that same product manager, facing that same terrifying red number, but this time, the dashboard has a voice. It doesn't just show the drop; it offers concise, automated explanations alongside it: "The 15% dip is correlated with a slowdown in new sign-ups from the US market."

Suddenly, the panic subsides. That one sentence, provided by powerful contextual insights, replaces a day of frustrated Teams messages and guesswork. It turns a passive reporting experience into an active decision-making process.

To unlock these sorts of contextual insights in practice, however, you need a BI solution with the right AI-powered features (also known as augmented analytics) to make them possible.

What is natural language query (NLQ) and how does it empower non-technical users?

What if your software users or product manager’s next question isn’t one your dashboard was designed to answer? This is where natural language query (NLQ) comes in. 

NLQ is one example of how modern BI features are making data more conversational, by turning a passive report into a dynamic dialogue.

Imagine your users could simply type, "What is chart revenue by month, show values over x?", and the analytics solution is able to return an easy-to-understand answer? That’s no SQL. No complicated filters. Just a simple question asked in plain English and typed in free text. 

With Yellowfin they can, using our in-built AI NLQ tool that automatically structures questions with the proper syntax on behalf of the user. It then generates an answer in the form of an interactive chart, graph or report. Your users can even click, drill, and filter the results for immediate exploration of their data, or further querying.

If they don’t know what type of question to ask, they can use AI NLQ’s Suggested Button sub-feature to instantly generate a list of helpful prompts, and use these questions and the generated results as a starting point to build more specific questions.

Having NLQ as part of your analytics solution shifts the power from your technical teams to your app users, enabling them to query, explore, pivot, and uncover contextualized insights on their own. 

For ISVs, this type of capability can make your product an indispensable tool for every user, driving further adoption and retention. It can be the difference between waiting days for an answer, and getting it in seconds.

How can AI help me analyze my data?

It’s one thing to ask a question, and another for the data to volunteer insights you didn’t even know to ask for. 

Solutions like Yellowfin have infused AI-powered analytics features such as Tell Me About My Data (TMAMD) to deliver helpful commentary about the data collected in your dashboard, report or charts. 

But instead of just delivering an answer, TMAMD proactively analyzes your data and serves up an actionable narrative of key trends, anomalies, and correlations in plain English - with a click. 

It’s like having a data scientist embedded in the dashboard, quietly pointing out the most interesting and crucial parts of your data story. 

Once your analysis is complete, your users can select and import the commentary and charts they want to use in other Yellowfin content, like dashboards, reports, Stories, and Presentations. This adds instant context to the numbers for them and their collaborators to further expand upon, and helps more people build data stories with AI.

The best part about embedding these AI-powered analytics features? Your users don’t need to have coding knowledge to get started, adding significant usability and value to your product experience.

What does the future hold for BI?

The future of business intelligence relies on providing more meaningful data. The most powerful BI platforms don’t just present metrics on a dashboard, but provide AI-powered tools to help your users uncover the full story behind the numbers, and deliver truly contextual insights. 

By weaving technologies like automation, machine learning and NLQ into the user experience, the analytics you are investing in will make data a source of clarity, not confusion, and empower your users to more confidently use it for decision-making (and value your software even more).