Training Industry Magazine - July/August 2020 - 38

Filling
Gaps
in the

The Most Important Data
and Analytics Capabilities
for Today's Companies
By Mike Galvin

Every day - and every moment - large
amounts of diverse data are being
generated and collected by companies
around the world. This data has a lot of
potential business value if companies
can appropriately utilize it. Naturally, this
growth in data is causing an evolution of
certain skill sets in order to meet a rapid
and ever-changing market demand, and
it's important that everyone learns at
least the basics of data analytics.
In essence, the data is there; the problem
is that you need employees who have
the skills to leverage that data and use
relevant tools to get it done efficiently.
This skill gap applies to everyone within
an organization. All roles are changing
to have basic data literacy requirements,
even if you've never previously worked
with data. And for those who do regularly
work with data, there's a growing need to
stay up to date on tools and techniques
as the field evolves.
So, what are some of the most in-demand
data analytics skills? Let's review three
of the most popular training topics I've
seen while working with corporate
clients in recent years.

In-demand Data Science
and Analytics Skills
Data Literacy
Data literacy is the ability to read,
analyze, work with and argue with data.

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Basic data literacy skills are needed in
every role no matter the organization.
Like other fields of study, there can be
varying levels of data literacy. At a basic
level, everyone should know common
terminology, types of data, where data
comes from, how data is used, and basic
analysis and visualization techniques.
This results in employees being able to:
*	 Speak fluently about data analytics
and its uses.
*	 Identify business opportunities and
make more data-driven decisions.
*	 Ask questions and evaluate proposed
solutions.
*	 Increase understanding of how data is
being used in their organization and
how decisions are made.

Python
Python is today's fastest growing
major programming language and is a
favorite with data practitioners. In fact,
according to Burtch Works, a leading
executive recruiting agency specializing
in data science and analytics, Python is
now the programming language most
preferred by data professionals. Most
major companies worldwide are using
Python, and an increasing number of
companies of all sizes report using it as
their primary programming language.
There are many reasons for this
widespread adoption. Python is open

source and has a large community of
active users. Its flexibility makes it useful
in multiple domains, and it has a large
number of open source libraries that
provide ready-to-go solutions for many
common problems. Not to mention,
Python has simple syntax and readability,
so the learning curve is low. All of these
things combined make Python an
attractive language for anyone working
with data within a company.

Basic data literacy
skills are needed in
every role no matter
the organization.

Machine Learning
Machine learning is a subset of artificial
intelligence that involves computers
learning from data. It's been around for
decades but has increased in popularity
over the past 20 years due to larger
volumes of data, improvements in
hardware, and the development of tools
for model development and deployment
that decrease the barrier to entry.
Machine learning has applications in all
parts of business including marketing,
advertising, supply chain, information
technology, human resources, finance
and more.
https://www.burtchworks.com/2019/08/21/2019-sas-r-or-python-survey-update-which-tool-do-data-scientists-analytics-pros-prefer/
Training Industry Magazine - July/August 2020

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