!!! Overview
[{$pagename}] is [data] that a process is applied to which makes the [data] useful.


!! [Data] and Five V's
* Value - value or validity meaning is the [data] correct and accurate for the intended use. Clearly valid data is key to making the right decisions. 
* Variety - [data] comes in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. This variety of [unstructured data] creates problems for storage, mining and analyzing [data].
* Volume - [Big data] implies enormous volumes of data. It used to be employees created data. Now that data is generated by machines, networks and human interaction on systems like social media the volume of data to be analyzed is massive. 
* [Velocity] - Data Velocity deals with the pace at which data flows in from sources like business processes, machines, networks and human interaction with things like social media sites, mobile devices, etc. 
* Veracity - [Data] Veracity refers to the biases, noise and abnormality in [data]. Is the [data] that is being stored, and mined meaningful to the problem being analyzed.
A reduction in "volume" takes place with [{$pagename}]. 


Ideally only [{$pagename}] for solving the problem is presented. 

Variety may, or may not, be reduced, depending on the screening process used in filtering the [data]. 

Value, velocity, and veracity (accuracy) should all increase with the decrease in volume.

[Machine Learning] allows organizations to filter and perform [Data Classification] on [Data-lakes] and [Data warehouses], creating [{$pagename}].


[Analytics] can be applied to [{$pagename}] where [Analytics] on poorer or to voluminous [data] may not be helpful.




!! More Information
There might be more information for this subject on one of the following:
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