Database Reference
In-Depth Information
The highlighted bubble represents a hospital, and the three metrics used
to size and position the bubble are shown in the tooltip. The connection to
the bar chart becomes obvious as Russell Hospital is identified as one of the
largest hospitals by bed size. This particular data point may not be the most
interesting or unexpected in this chart, yet now you have a much better sense
of what the data product is trying to convey about hospitals.
It is often said that you know you have become fluent in a foreign language
when you dream in the language. Novice language learners often translate
their new language back into their mother's tongue word for word. Translating
back to one's native tongue, while a crutch, is often needed for a time until
one increases in fluency. Gaining data fluency is like developing language
fluency. Without instant recognition of the meaning of a data visual, it can be
useful to convert the information into a language in which you are familiar. In
time, translating back isn't necessary.
Referring to Figure 4-21 to understand the message in the data, you might
translate a highlighted data point into a descriptive sentence such as “Russell
Hospital has 730 beds, tied with three other hospitals” or “Russell Hospital's
patience experience score is near the top of all hospitals shown.” This is a way
of capturing and testing your understanding of the data depicted.
By breaking a complex data product into its smallest pieces and finding some-
thing comprehensible, you can start to understand both what the author is
trying to show and how to read the content.
What Can You Do with It?
You are left with the job of sorting the good from the bad. Distinguishing
between a data product that is useful and one that is distracting—one must
understand whether it is reliable and/or valid. With reliability and validity
determined, data products must be actionable.
Reliability and Validity
When considering whether you should use data, you first need to determine if
it is reliable and valid. Reliability refers to the extent to which a measurement
procedure yields consistent results; that is, if a particular technique, applied
repeatedly to the same object or phenomenon, produces the same result
each time. 6 For example, you could think of using a scale to weigh yourself.
If you stepped on the scale 10 times in a row and recorded your weight each
time, a reliable scale would give you the same result. If, however, the recorded
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