The Data Fluency Framework - Data Fluency: Empowering Your Organization with Effective Data Communication - page 28

On a much smaller scale, successful data fluent organizations create an ecosys-
tem that enables the creation and sharing of data products. The objectives are
similar to Apple's app store: Ensure quality data products; allow distribution of
the right data to the right decisions makers at the right time; and encourage
curation of data products so the most valuable ones are discovered and used.

The ecosystem requires three fundamental conditions: standards, tools, and
processes. Standards are the design patterns and style guidelines that make
it easier for data producers to effectively communicate with data. The best
tools make it efficient to design and build data products and ensure they are
discoverable for the target audience. Processes encourage sharing of insights,
collaboration between producers and audiences, data hygiene, and quality
control. A healthy ecosystem can help facilitate data fluency throughout the
organization. Chapter 7 reviews these fundamental conditions and provides
specific guidance for organizational leaders to create a data fluent ecosystem.

CONNECTIVE TISSuE

The elements of the framework are linked together by guidelines, tools, stan-
dards, and training. For example, the data fluent organization needs to define
and create training resources to help individuals learn basic data comprehen-
sion skills. Likewise, the design standards defined in the ecosystem should result
in a style guide that data product producers use to standardize their output.

RESOURCES FOR MORE DEPTH

The objective for this topic is to explain all the elements that must come
together to create data luency for your organization. As a result, this topic
provides a comprehensive solution for each of the elements in the framework.
Fortunately, most of the resources about data communication, data visual-
ization, and data-driven enterprises take a narrower and deeper view. The
following topics and websites can ill out your knowledge of the elements
in the framework.

Data Literate Consumers
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Michael Milton, Head First Data Analysis (O'Reilly Media, 2009)

Alistair Croll, Benjamin Yoskovitz, Lean Analytics (O'Reilly
Media, 2013)

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