Data Stories Add Context to the Numbers

A splash of data used to be all you needed to get attention. Today, data-smart audiences want much more: detail, what-if scenarios, and deep, multi-sourced data for any questions they may have. They also want to see your work, from initial questions to final insights. 

What they want is what people have always wanted: stories. For data, that means data stories. People live and breathe stories, whether they’re aware of it or not. So it’s inevitable, now that business people have tuned in to the “data-driven” ethos, that they would want “data storytelling.” 

Good stories are not only understood, they’re also remembered, and the really good ones are even retold. Unfortunately, too many people hear “story” and assume it’s a sequence of visualizations. Data storytelling actually begins at data discovery, runs all the way through data analysis to the end at presentation.

The implications go deep.

Good data stories incite conversation

Even better data storytelling incites conversation. While a good story makes an audience sit up, listen, and live the data, an even better story brings out the questions. Hands shoot up. “Did you include the latest data from that new region?” they ask, “They’re doing better out there than early numbers said.”

You get to show your stuff. You lead the conversation with the full, rich set of data you found in so many corners of your organization. Stories that engage the audience let them help to create a new story. That’s what they understand the best, remember the best, and are more likely to retell.

Good data stories frame questions

What surprises most people about data stories is that they work their influence during data discovery — even before any data analysis happens at all.

We all frame questions based on the stories that run through our heads — usually so quickly and naturally that we’re not even aware of it. Those first-round stories determine what you think is important, what questions you ask, and data you look for.

For example, a case shown in the data storytelling class at TDWI conference is about declining bank balances. There, bankers ask why account holders are pulling money out of savings. Questions arise from the imagined or observed scenarios, or stores: the house down payment, the tuition, or the crisis. Then they look at that data. Once confirmed, they look at other data to test ways the bank might help.

Telling the whole story

Better narratives arise from deeper, richer texture in the data. Too often, analysts only look at a small subset of the data that is familiar, possibly in a spreadsheet they have developed and nurtured. It’s too challenging and time-consuming to find and understand other data sources in the enterprise.

This is where Attivio helps out. Attivio democratizes data, by providing self-service data discovery. It’s fast, it’s easy, and the foundation is a universal catalog of all enterprise data. Analysts can build data marts just like shopping on Amazon.com.

Then they have the advantage of using the best enterprise data available, so they can tell the whole story, with confidence.

TDWI Chicago

Data storytelling is the subject of a popular new class at the TDWI conferences — including TDWI Chicago May 8-13. I’ll be there, so stop by the Attivio booth for a chat. And take a look at the class, Data Storytelling: The New Horizon in Business Analytics. Taught by Dave Wells and Ted Cuzzillo, it takes place on Friday, May 13.

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