Training Industry Magazine - Winter 2023 - 55

The interpretation
of data leads to
information, which
in turn, leads to
knowledge.
The Need for Data
Literacy Training
Given the broad application of all types
of data throughout an organization and
its proven benefits, it is necessary that
data literacy training takes place at all
levels of an organization. Individuals
from senior-level executives to the most
junior member of the association must
have data literacy training.
It is also critical to make data literacy
training a part of each organization
member's annual training plan and
make data literacy part of each new
employee's onboarding process.
* Volume: This refers to the volume of
new data being created and captured.
* Value: This refers to the perceived
value the data contains. This often
refers to the relevance of the data to
its intended usage.
* Veracity: This refers to the overall
quality of the data.
* Variety: This refers
to the various
forms and types of data that are being
created and captured.
Data is constantly changing and its
usage evolving to meet the needs of
every organization.
Figure 1.
What
Happened?
Descriptive
Analytics
Diagnostic
Analytics
Predictive
Analytics
How Did
It Happen?
What Will
Happen?
What Should We
Do About It?
Cognitive/
Prescriptive
Analytics
Self-Learning
Analytics
The Many Facets of
Data Literacy
Data literacy has many facets that must
be addressed in any data literacy training
program. The range of facets and the skills
necessary are broad in scope.
These skills include such areas as where
to find data, how to validate the data,
assessing the relevance of the data to
the information being desired, how to
clean, organize and categorize the data,
how to analyze and interpret the data,
how to present the data, etc.
Data Literacy Training
organization
Data literacy training should prepare
each
member
to
feel
comfortable and confident in using data
to conduct their responsibilities and
have a high level of confidence when
presenting their analysis of the data and
associated recommendations.
All data literacy training must be
purpose-driven training. Initial data
literacy training can utilize online
training (virtual training) to reach as
many organizational members as
quickly as possible to establish a baseline
of minimal knowledge. The training
should also be designed to meet not
only the current but also the future data
needs of the organization as the overall
organization data maturity increases.
(See Figure 1.)
More advanced data literacy might
benefit from in-person training to
communicate more complex aspects of
data literacy.
Here are some examples of data literacy
training components:
* Data source identification.
* Data validation.
* Data cleaning, organizing and labeling.
* Data version control.
* Understanding the organizational
data need at both the strategic and
tactical levels.
What Don't
I Know?
Requires Increasing Levels of Organizational Data Literacy
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Training Industry Magazine - Winter 2023

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