Home' Army Acquisition Logistics and Technology Magazine : Army ALT July-September 2016 Contents framework of infrastructure, platform
a nd soft wa re applications (or “apps”).
Consider the following: This morning,
you probably awoke to an alarm that you
set on your mobile phone. In addition,
you probably reviewed email messages
or read today’s headlines over coffee. Per-
haps you checked the weather or traffic
before leaving home for the day. All on
the same device.
You probably rely on several apps on your
phone to improve productivity a nd qual-
ity of life. What you probably do not
think about is how different organiza-
tions develop each of these apps across
a very diverse and competitive industry.
Most modern software development
efforts are based on a NIST-type modular
framework, where applications are built
to operate on a common, shared plat-
form. For exa mple, Apple iOS, Android,
Xbox and PlayStation are platforms that
provide an environment in which inno-
vation can flourish. The environment in
which an app is created and deployed is
completely separate from the app itself.
This environment includes not only the
platform, but an entire development sys-
tem that encourages seamless integration.
The user doesn’t see this technical nuance,
but it’s enormously important when con-
sidering life cycle costs and quality.
With software sustainment, the choice
of platforms is the linchpin that allows
for versioning, expansion, adaptability
and flexibility. A robust platform enables
independent apps to have limited deploy-
ments that can scale to a large user base
when ready. In the same way, applica-
tions can be added or removed without
impact to related services. Using a com-
mon platform is a distinct tradeoff for
end users. Applications will be limited
to platform services; however, more indi-
viduals can participate in development.
BIG DATA GLOSSARY
Analytics. The synthesis of knowl-
edge from information. Analytics is
used to refer to the methods, their
implementations in tools, and the
results of the use of the tools as inter-
preted by the practitioner. An analytic
is one of those tools.
Big data. Consists of extensive data
sets—primarily in the characteristics
of volume, variet y, velocity and/or
variability—that require a scalable
architecture for efficient storage,
manipulation and analysis.
Cloud. Computing that is done
through a number of computers linked
together and accessed through the
Data science. The extraction of
actionable knowledge directly from
data through a process of discovery,
or hypothesis formulation and hypoth-
Data scientist. A practitioner who
has sufficient knowledge in the over-
lapping regimes of business needs,
domain knowledge, analytical skills,
and software and systems engineer-
ing to manage the end-to-end data
processes in the data life cycle.
Distributed computing. A computing
system in which components located
on net worked computers communi-
cate and coordinate their actions by
Hadoop. A free, open-source
Apache Software Foundation plat-
form that can deal with large amounts
of semistructured and unstructured
data, and data that needs a data
discovery process in order for it to be
Horizontal scaling. To make use
of distributed individual resources
integrated to act as a single system. It
is this horizontal scaling that is at the
heart of the big data revolution.
Open-source software. Soft ware
for which the original source code is
freely available. Such software may
be redistributed and modified, and is
continuously improved or adapted by
the programming community.
Open-standards architecture. An
architecture development approach
that utilizes open standards to reduce
the cost and risk of ownership of
weapon systems, delay system
obsolescence and allow fielding of
capability more quickly.
Parallel computing. A group of com-
puters linked together for processing.
Also called parallel processing.
Vertical scaling. Increasing the sys-
tem parameters of processing speed,
storage and memory for greater
(SOURCE: National Institute of Standards
and Technology, TechTarget.com, Oxford
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