Data Stories

Data storytelling is communicating the meaning of a dataset with visuals and a narrative that is customized for a particular audience.

A data-storytelling narrative connects the data to the project objectives.

3 data storytelling ways

  1. Engage the audience

    Capturing and holding the audience's interest and attention

  2. Create compelling visuals

    Spotlighting involves scanning through data to quickly identify the most important insights.

    This can be done with notes on a whiteboard, by searching for broad ideas, and by identifying concepts that arise repeatedly.

  3. Tell the story in an interesting way

Live and static insights

S​tatic data involves providing screenshots or snapshots in presentations or building dashboards using snapshots of data.

PROS

  • Can tightly control a point-in-time narrative of the data and insight

  • Allows for complex analysis to be explained in-depth to a larger audience

CONS

  • Insight immediately begins to lose value and continues to do so the longer the data remains in a static state

  • S​napshots can't keep up with the pace of data change

L​ive data means that you can build dashboards, reports, and views connected to automatically updated data.

PROS

  • Dashboards can be built to be more dynamic and scalable

  • Gives the most up-to-date data to the people who need it at the time when they need it

  • Allows for up-to-date curated views into data with the ability to build a scalable “single source of truth” for various use cases

  • Allows for immediate action to be taken on data that changes frequently

  • Alleviates time/resources spent on processes for every analysis

CONS

  • Can take engineering resources to keep pipelines live and scalable, which may be outside the scope of some companies' data resource allocation

  • Without the ability to interpret data, you can lose control of the narrative, which can cause data chaos (i.e. teams coming to conflicting conclusions based on the same data)

  • Can potentially cause a lack of trust if the data isn’t handled properly

Dashboard

A dashboard is used to track, analyze, and visualize information.

To automatically resize the layout based on the dashboard size, the analyst should use a tiled layout. In Tableau, tiled items create a single-layer grid that contains no overlapping elements; floating items can be layered over other objects.

You might choose to use filters in order to highlight individual data points or to zero in on what's important to your stakeholders.

When designing a dashboard, data analysts can ensure that charts and graphs are most effective by placing them in a balanced layout and making good use of available space.

Presentation tips

The following aspects should be considered when you make a presentation.

  • Characters: The people affected by your story

  • Setting: Background information about the data project that describes the current situation

  • Plot: Conflict that creates the tension in the current situation

  • Big reveal: Resolution that solves the problem

  • Aha moment: Moment that you share your recommendations and explain why.