$ framework of 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, variety, 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 internet.
Data science. The extraction of actionable knowledge directly from data through a process of discovery, or hypothesis formulation and hypoth- esis testing.
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 networked computers communi- cate and coordinate their actions by passing messages.
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 analyzed.
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. Software 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 performance.
(SOURCE: National Institute of Standards and Technology,
TechTarget.com, Oxford Dictionaries,
businessdictionary.com,
acqnotes.com)
infrastructure, platform and software applications (or “apps”).
Consider the following: Tis 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 and 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 example, Apple iOS, Android, Xbox and PlayStation are platforms that provide an environment in which inno- vation can flourish. Te environment in which an app is created and deployed is completely separate from the app itself. Tis environment includes not only the platform, but an entire development sys- tem that encourages seamless integration. Te 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.
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