The Pragmatic Definition Of Big Data

Big Data Definition, Mike Gualtieri, ForresterForget About The Three Vs

Big data is not defined by how you can measure data in terms of volume, velocity, and variety. The three Vs are just measures of data how much, how fast, and how diverse? A quaint definition of big data to be sure, but not an actionable, complete definition for IT and business professionals. A more pragmatic definition of big data must acknowledge that:

  • Exponential data growth makes it continuously difficult to manage — store, process, and access.
  • Data contains nonobvious information that firms can discover to improve business outcomes.
  • Measures of data are relative; one firm’s big data is another firm’s peanut.

A pragmatic definition of big data must be actionable for both IT and business professionals.

The Definition Of Big Data

Big Data is the frontier of a firm’s ability to store, process, and access (SPA) all the data it needs to operate effectively, make decisions, reduce risks, and serve customers.

To remember the pragmatic definition of big data, think SPA — the three questions of big data:

  • Store. Can you capture and store the data?
  • Process. Can you cleanse, enrich, and analyze the data? 
  • Access. Can you retrieve, search, integrate, and visualize the data?

Hear me explain this definition on a special episode of Forrester TechnoPolitics: The Pragmatic Definition Of Big Data Explained

Comments

Store may be optional

With streaming data technology "store" is not entirely mandatory in terms of gaining insight from big data

At last, a pragmatic view of

At last, a pragmatic view of Big Data. Here at import•io we hit "process" and "access" on your pragmatic definition of big data. See http://import.io/launch/

Pragmatic but not specific to big data

The problem with this definition is that it has nothing to do with big data, per se. The idea of big data matters because its volume, variety, and velocity necessitate new technologies that combine features like scale-out, non-relational, and low latency.

Your pragmatic definition really applies to data management as a whole, not specifically to big data.

From SPA to SPU?

Hi, a very good read. I might tune up the last letter from A to U:
Access to Use

In order to Use data for some purpose you pragmatically go through layers (like peeling off the onion):

Awareness - how did it came to my mind to need/search for the data (push or pull)
Find - where is the data and how to get...
Access - even if I know where it is - can I access (rights, technology, language - I cannot read Chinese that well)
Content - is the quality of the content adequate? Swet or bitter onion :-?

SPU = SPAFAC
BR. Heimo

well in data base

well in data base terminology, we have CRUD acronym which is stand for Create data, Read data, Update Data, and Delete data.
this is the basic function of database. we can make application or just use simple excel to do that.

but big data is different. because the data is big, you can't exploit them with simple tools or you can do that with your tools but it's cost a lot. that's why we called it big data because it need more advance tools in the term of capacity to exploit and other