Data Authors: Skilled Designers of Data Presentations - Data Fluency: Empowering Your Organization with Effective Data Communication - page 83

take shape based to a large extent on the underlying data. And as this data
changes, the emphasis and message of the visualization is likely to change.

Therefore, communicating with data is less often about telling a specific story
and more like starting a guided conversation . It is a dialogue with the audi-
ence rather than a monologue. While some data presentations may share the
linear approach of a traditional story, other data products (analytical tools, in
particular) give audiences the flexibility for exploration. In our experience, the
best data products combine a little of both: a clear sense of direction defined
by the author with the ability for audiences to focus on the information that
is most relevant to them. The attributes of the traditional story approach
combined with the self-exploration approach leads to the guided safari anal-
ogy (Figure 5-2).

Communicating with data is like creating a guided
safari. On a guided safari your guide (the data product
author) takes you down a path in which he thinks
there will be a good chance to see wildlife. If you
are on a guided safari in the Serengeti, you may be
searching for the big five: elephants, lions, cape buf-
falo, black rhinos, and leopards. The tourists are led
to places where the animals are likely to congregate,
near food sources or watering holes. The safari guide
knows the best places to look, but the story will
change every day. The data product author's role is
to create and lead an audience to a target-rich envi-
ronment for finding data stories. It is up to audiences
to recognize stories that are relevant to them.

Traditional Story Traditional Story Self-exploration Guided Safari

Figure 5-2: Analogies for storytelling and data visualization

Having considered your role as a data author in an environment with multiple
influences, now turn to six core principles for creating an effective data product:

1. Find the purpose and message of your data products and know your
audience .
2. Be discriminating with what data you present.
3. Define metrics that are meaningful and can lead to action .
4. Create a logical structure and narrative flow to your data product.
5. Master basic design skills for making your data presentation attractive and
easy to understand , including choosing the right form and language to
present the data.
6. Create data products that serve a broader audience and start a dialogue .