Whether you’re part of a small business or a large one, big data is important. Even small businesses are finding they now have access to many of the same tools as very large corporations, and they’re using it to their advantage. Being able to afford big data resources and analytics tools is no longer out of reach for small organizations.
With that being
said, just because the tools and resources are there, it doesn’t necessarily
mean all organizations are using them correctly or that they’re staying current
with how to use data.
The following
are some data trends and other things to think about in 2019, whether you’re an
analyst or someone who’s in a different role in a small, large or medium-sized
business but who wants to harness the power of big data effectively.
The Growth of Cloud Computing
Data may have
outgrown the name “big data” in many ways because it’s not just big. It’s
pervasive and it’s everywhere in the background of every organization, whether
people realize it or not. There was a fear that this ever-growing nature of
data in the business world (and everywhere else) would be difficult to keep up
with in terms of cloud
computing, and potential infrastructure shortcomings.
The process to
bring data from the perimeter of the IT infrastructure and to the cloud can
take a long time, but there has been a focus on creating new infrastructures
that reduce this lag time in a cost-efficient way and make the move from the
perimeter to the cloud more efficient overall.
With all that
being so pertinent right now, it’s important that companies have the storage
and processing tools to make it happen.
What all this
boils down to is an increasing
need for edge computing. Edge computing in simplest terms is computing done
near the source of data or perhaps even at it. This is a shift away from the
cloud in reality, but the cloud isn’t likely to lose its important role in how
businesses and the world do things.
Edge computing
is just incredibly fast, and it can offer some advantages regarding privacy and
security as well.
Machine Learning Isn’t Necessarily That Important…Yet
For the past few
years, you’ve probably heard a lot about machine learning. However, just
because the algorithms provided by machine learning are advancing quickly, it
doesn’t mean that old-fashioned analytics are dead.
Machine learning
is driven toward achieving very specific goals, but we’re not at the point
where it can necessarily take those specific tasks and goals and apply them to
real-world situations in the way that humans can.
The Risks of Dark Data
The potential
risks that come with dark data are very relevant right now. Dark data is any
digital information an organization is storing that’s not being used. It’s the
data your organization collects and stores as part of doing business, but isn’t
using it for any purpose currently.
There are plenty
of reasons an organization might leave dark data hanging around. The business
may outgrow the need for that data before it’s used, or it may no longer be
relevant for some reason. The data might be incomplete, or it may be stored in
places that are no longer in use.
There are risks,
however. If dark data is being stored there are security concerns that need to
be addressed. Along with the security risks, dark data may also represent
opportunities that aren’t being utilized.
The Rise of the CDO
There is likely to be
so much focus on data in 2019 and beyond that many companies will begin
hiring someone to be in charge of it all. This position is often referred to as
the Chief Data Officer or CDO. Some organizations may already have a CDO, but
that position is likely to grow and expand in the future.
Hybrid Cloud
Finally, while
the fact that the cloud is less relevant in the face of edge computing, it’s
certainly not obsolete. One trend in the world of the cloud is something called
the hybrid cloud. The hybrid cloud combines
elements of a private cloud with a public cloud. The benefits of a hybrid
cloud can include increased flexibility, options, and tools. With a public
cloud, the applications for use can include projects that don’t require a high
level of security.
For on-premises
private cloud, the applications can include the more sensitive information that
needs a high level of privacy and security.
Image Credits: Data Trends from Tonktiti/Shutterstock
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