Tech evangelists are currently pounding their pulpits about
all things AI, machine learning, analytics—anything that sounds like the future
and probably involves lots of numbers. Many of these topics can be grouped
under the intimidating term data science, but all that really means is testing
hypotheses to make better business decisions.
Not so bad, right?
Let’s dispel any dread you may have regarding data science
even further. Here are five misconceptions about data science you can
confidently sidestep to make data science a practical addition to your own
False: It’s hard to find
Companies don’t need to hire folks with Ph.D.s in math or
statistics to apply data science to their business, they can start with the
resources they already have: the dedicated and disciplined software development
teams. These teams specialize in providing business solutions that deliver
value, so pivoting a team to focus on data science is not an unreasonable request.
False: Data science
is only meant for large organizations
Data science doesn’t require expensive hardware, software,
or expertise. It’s not about the number of resources, it’s about having smart
people who can apply data science competently.
False: Data science
is a fad
Data science didn’t burst onto the scene from nothing. It’s
a cumulative result of decades, if not centuries, of statistics, forecasting,
and more. What makes data science unique today is the nearly unfathomable
amount of data available, impressive computing power, and widely available
False: Complex models
are better than simple ones
Simpler models can be more efficient, cheaper to process,
and easier to conceptualize and explain than complex ones. Unnecessary
complexity can yield diminishing returns and endless model tweaking.
False: You need a
deep understanding of statistics and statistical methods
It may have been a few years since your developers last
touched statistics, but they can always refresh their knowledge through online
resources like e-books (here’s one
on statistical learning, and here are a few from Syncfusion 
and courses. From
there, they can build models that fit the unique needs of the organization.
Still not convinced data science is something your business
can undertake? Read “10
Myths About Data Science,” a white paper by Syncfusion Vice President
Daniel Jebaraj, for a more in-depth look at the misconceptions refuted here,
plus five more falsities that may be holding you back from making data science
a valuable part of your business strategy.