From data to story

How can you publish data in a format that meets the needs of your users?

While some users may want raw data (actual figures that can be used to create bespoke graphs and charts for example), others, particularly non-analysts, those with limited analytical skills or those with limited time for analysis, may want headlines, insights or stories, alongside (or instead of) actual raw data.

From data to story

Turning raw data into something we can use to make a decision or form an opinion means deciding what to show, what to emphasise, and what to filter out.

• Data = a number, statistic or measure (quantitative); a fact, an opinion or experience (qualitative)

• Metric = data with specific parameters, type of measurement

• Information = metrics with context

• Insight = information with implications

• Story = connected insights

The value of data increases as it turns into a story, because a story helps connect the dots between and paint a picture with single units of data. Those who work with data must be able to communicate why it is important or useful, otherwise the value is lost.

For more information about developing data stories, try this: a four step approach to storytelling with data.