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BY NETCOM LEARNING

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INTRODUCTION
WHAT IS DATA SCIENCE AND WHY IS IT IMPOSTANT FOR ORGANIZATIONS?
HOW MUCH OF AN IMPACT DOES A DATA SCIENTIST HAVE ON THE SUCCESS OF
MAJOR PLAYERS LIKE FACEBOOK, GOOGLE, AND LINKEDIN?
COMBATTING DATA SCIENCE SKILLS GAP
NETCOM LEARNING EXPERTISE
SUMMARY AND FINDINGS
Contents
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Statistics, Machine Learning, Data Science, or Analytics – whatever you call it, this discipline is on rise for the past few years.
Researches show that 90% of the entire world’s data was created in the last couple of years. And while billions are being spent on
making sense out of these available data, less than 0.5% are getting analyzed and made use of.
This increase of data collection abilities and exponential computational power have drawn attention from organizations. It is
becoming clear by the day that the value lies in processing and analysis of data, and even though executives have heard of
about data science, most are still unaware of the value a data scientist holds in a corporation.
Introduction

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It is the age of analytics and we are competing in a data-driven world. Data and analytics capabilities have made a leap forward
in recent years. The volume of available data has grown exponentially, more sophisticated algorithms have been developed, and
computational power and storage have steadily improved.
But to correctly use and apply the power of Data Science, an organization will need the right data, the business will, and varied skill
sets like developer, statistician, business analyst, data engineer/architect, and project manager. Further, no one's happy unless this
can be done at scale and speed, and applied to many areas of the business.
Most data scientists in the industry have advanced degrees and training in statistics, math, and computer science. Their
experience is a vast horizon that also extends to data visualization, data mining, and information management. It is fairly common
for them to have previous experience in infrastructure design, cloud computing, and data warehousing.
What is Data Science and why is it
important for organizations?

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Here are instances when a company can benefit from having a data scientist:
• When there is a need to crunch large volumes of numbers
• When possessing lots of operational and customer data
• When they can benefit from social media streams, credit data, consumer research or
third-party data sets
As suggested by Gartner, The data scientist role is critical for organizations looking to extract
insight from information assets for “big data” initiatives and requires a broad combination of
skills that may be fulfilled better as a team, for example: Collaboration and team work is
required for working with business stakeholders to understand business issues. Analytical and
decision modeling skills are required for discovering relationships within data and detecting
patterns. Data management skills are required to build the relevant dataset used for the
analysis.
Data science is a discipline that incorporates
varying degrees of Data Engineering, Scientific
Method, Math, Statistics, and Domain Expertise - It
brings the prospect of solving business problems
with math. Along with that comes more advanced
application development that blends rules-based
decision patterns and machine learning.

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Eight ways a Data Scientist can add
value to any business:

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How much of an impact does a Data Scientist
have on the success of major players like
Facebook, Google, and LinkedIn?
What sets apart a Data Scientist from a seemingly similar Data backed job is that while a data statistician is concerned with past
movements and interpretation of data, a Data Scientist is more mathematically focused on providing an insight into future patterns
identified from historical and real time data. The role of a Data Scientist is part analyst and part artist, set to revolutionize the way
the data processed and used.
The huge success of professional networking site LinkedIn is a prime example of the immense benefit that data scientists are
bringing to business intelligence. As an organization that relies primarily on the data transferred by its 380,000,000 users making
connections with each other, LinkedIn is utilizing those professionals with the training and curiosity to make discoveries in the world
of big data.

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LinkedIn, alongside other large knowledge industries such as Facebook and Google, is utilizing
the role of data scientists to bring structure to large quantities of unstructured and
unorganized data and to determine significance in its value, and systematic relationships
between the variables.
A recent survey of C-suite executives by NewVantage conducted in 2016 has revealed that
99% of the respondents thought analysis of big data was important to their strategy next year.
In the decade where enterprise data is expected to exceed 240 exabytes per day by 2020,
as per a report from CISCO published in June 2016, the need for data scientists with the skills
to extract valuable insights from this data is more important than ever.
However, the demand for data scientists is very much exceeding the supply and that
companies in the United States alone will need to hire between 140,000 – 190,000 data
scientists if they are to keep up with the new data demand.

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The technology sector is facing challenges as it struggles to fill a growing demand for data scientists.
McKinsey Global Institute predicts that the shortage in the U.S. could increase to 250,000 data scientists by 2024.
This skills shortage is a global phenomenon and the dearth of qualified talent is also driving up salaries - data scientists in the US can
expect a six-figure starting salary, while recruitment website Glassdoor has ranked data scientist as the top profession for the past
two years, based on job openings, salary and overall job satisfaction.
Education and professional training are struggling to catch up with industry's demands. About 8,000 people in the US are
graduating each year with master's degrees in data science or data analytics, which is a pitifully small number considering the
scale of the shortage, as experts estimate 100,000-190,000 data science jobs will go unfilled in the United States alone, from 2011
to the end of this decade.
Combatting data science skills gap

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As wonderful as it would be to have a simple, straightforward solution, a problem this complex features many different
approaches, each with its own advantages and disadvantages. Compounding the issue is the fact that each organization
functions different and has its own set of challenges and obstacles to overcome. So, one-size-fits-all strategy simply doesn’t exist.
There are, however, several ideas and solutions that have cropped up in recent years meant to address this skills gap.
One strategy might be to take employees that already work for the company and train them in the art of using big data. Of
course, building someone up from scratch might not be the most efficient means of getting big data talent, but if an employee
already has skill with programming, mathematics, and problem solving, getting them to become familiar with big data isn’t
necessarily a stretch. They must have an interest in the subject, of course, but the value this can add to the company outweighs
any investment needed for training.
As the demand for big data scientists grows, so too does the number of degree programs being offered by major educational
institutions. In fact, many big tech companies have opened partnerships with universities to develop data science programs
How Companies Can Address Shortage Now?

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designed to train the next generation of data scientists. This has the added benefit of not only getting students and prospective
data scientists the training they need to tackle big data problems, but it also opens an easy path to go from degree to first job out
of college.
This partnership idea is being implemented all over the world in some interesting ways. A Harvard-based startup, for example, is
looking to give students special apprenticeships wherein they work with industry leaders from giant companies like Apple and
Amazon to solve real world problems those companies are currently facing. Those can include analyzing data for customer insights
or participating in IT Transformation. The idea is to give students some hands-on experience with analytics projects they’ll be taking
on once they have graduated. It makes for a smooth transition and top-notch preparation for a long and successful career as a
data scientist.
While there is no one solution to bridging the big data skills gap, finding one remains a top priority. Businesses have great need to
have talented data scientists as part of their organizations. If the skills gap decreases, more companies will be able to take full
advantage of what big data must offer, providing a clear path to success well into the future.

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How can we help?
Training employees can be a relatively quick process and can be accomplished in roughly a year.
Companies can choose one or two platforms and can get there quickly.
Launch programs with NetCom Learning that train analysts to become data scientists:
Many organizations are flush with analysts who typically have some data science skills in key areas such as statistics, and are
starting Data Science Transition Program in partnership with NetCom Learning.
Our programs enable high-performing analysts to be apprenticed to a data scientist. From Data Science Essentials, to Machine
Learning algorithms, to Power BI, professionals learn data science skills on the job while taking advantage of our data science
solutions and training programs. At the end of the program, the participant becomes a Data Scientist at the company.
The NetCom Learning Expertise

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NetCom Learning is an innovative leader in IT, business, and executive training to companies, individuals, and government
agencies, dedicated to promoting the values of lifelong learning. NetCom Learning has trained over 80% of the Fortune 100 and
helped advance the skills of more than 90,000 professionals. NetCom Learning’s efforts at offering a customer-driven culture have
resulted in building a trust factor that can be seen in our high instructor evaluations of 8.6 out of a possible 9. Our instructors have
an average of 20.75 years of experience, and our courses have produced more than 2,300 client testimonials, with 96% of our
clients recommending our services.
Our quality customized learning solutions have earned us the respect of the learning industry, being named Microsoft's Worldwide
Training Partner of the Year, Inc. Magazine 5000's fastest growing company and TrainingIndustry.com's 2016 Top 20 IT Training
Company.

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An action plan to take charge of the skills gap
Big data has fundamentally changed the way businesses compete and operate. Companies that invest in and successfully derive
value from their data will have a distinct advantage over their competitors — a performance gap that will continue to grow as
more relevant data is generated, emerging technologies and digital channels offer better acquisition and delivery mechanisms,
and the technologies that enable faster, easier data analysis continue to develop. But as it is said, Big opportunities do bring big
challenges.
While there is data science skill shortage, there are learning partners who are constantly improving the workforce productivity by
their innovative learning frameworks.
Organizational leaders should look to these partners and their learning professionals to help identify the skills and competencies
needed now and in the future and to align their development to key drivers for the organization.
IT leaders need to start looking at alternative learning programs: In order to ensure that there are enough people who are capable
in data science, more high schools and universities will have to consider how they teach young people the necessary tech skills. By
Summary and Findings

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instilling this idea of "unconventional" online learning -- which becomes more conventional by the day -- students will be better
prepared for the expectation that once they enter the workforce, the learning doesn't stop. There is a need to grow the next
generation of analytics and big data experts and we need to start early.
The following action plan identifies six steps for taking charge of skills gaps
• Understand the organization’s or unit’s key strategies, goals, and performance metrics.
• Identify competencies and skills that map to strategies and performance metrics.
• Assess the skills gap.
• Set goals and prioritize the path to filling gaps.
• Implement solutions.
• Monitor and measure results and communicate the impact.
With all of these partners helping, organizations can obtain the skills they need for engaging, challenging, and well-paid work,
while fulfilling their responsibilities to further their professional development.

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Copyrights 2017 by NetCom Learning
NetCom Learning helps build innovative learning organizations in the
workplace by structuring a smarter workforce, supporting changes, and
driving growth. Since 1998 we have been empowering organizations to
reach optimal performance results and address challenges by managing
all aspects of organizational learning.
Learn more at www.netcomlearning.com