Training Industry Magazine - July/August 2020 - 39

Companies are increasing investment
in machine learning as they work to
improve decision-making, automate
processes and leverage untapped
sources of data. For many, machine
learning serves as a foundation to
improve understanding of customer
behavior, inform capacity and planning
decisions, and forecast performance.
Studies show that companies making
extensive use of analytics are far more
likely to outperform their competition in
sales growth and profitability.

Training is most
powerful when
companies use
real-world data and
use cases.

As mentioned previously, there are
many reasons for widespread Python
adoption. Python training leads to
benefits that can include increased
productivity, efficiency and innovation,
as well as decreased time to market.
As an example, CMA Strategy Consulting,
a boutique consulting firm focused on
the telecommunications, media and
high-tech industries, chose to train 75%
of its company in Python, from analysts
and managers to principals.
This was because CMA faced a growing
problem: Their clients' datasets were
getting too large and diverse for their
existing toolset. By training in Python, they
would be able to add the language into
their existing workflow, allowing them to
efficiently work with these larger datasets.
After the training, CMA was quick to
adopt the techniques learned, with
results indicating that analyses using the
team's new Python skills ran 22.5 times
faster than before.

TOP 3
IN-DEMAND
DATA SCIENCE &
ANALYTICS SKILLS

1
Data Literacy
The ability to read, work
with, analyze, and argue
with data

What to Look for in a Data
and Analytics Training
Provider
How Companies Use
Training to Solve
Common Problems and
Achieve Strategic Goals
Data literacy training will help generate
business value by enabling teams to:
* Make more informed decisions based
on data.
* Uncover actionable insights from
data and identify opportunities within
the business where data can be
leveraged.
* Increase collaboration in a data-driven
organization.
* Increase adoption and usage of datadriven solutions.
Machine learning training enables staff
to better leverage data. This can lead to
increases in innovation and reductions
in cost.

When it's time to seek out a training
provider for your team, there are a couple
questions and goals to keep in mind. First,
it's important to focus on outcomes. Ask
yourself, "What do I need my team to be
able to do after this training, and how do
those outcomes align with our overall
business needs?" You'll need to ensure
your training partner can address these
outcomes directly.
Additionally, training is most powerful
when companies use real-world data
and use cases for training purposes,
adding relevance and enhancing the
connection between the learning and
how these new skills will apply directly
to their work.
Mike Galvin is the executive director of
corporate training at Metis, where he
oversees the data science and analytics
training programs for all of Metis's
corporate clients, including Wells Fargo,
Intel and Fortune 500 companies across
industries. Email Mike.

2
Python
A major programming
language that is a favorite
with data practitioners

3
Machine Learning
A subset of artificial
intelligence that involves
computers learning
from data.

T R A I N I N G I N DUSTR Y MAGAZ INE -DATA FLUENCY IN LEARNI NG 2 02 0 I WWW. T RAI NINGINDU S T RY . C OM/ MAGAZ I NE

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Training Industry Magazine - July/August 2020

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