The marketing-coined term BigData is not just referring to the volume of the data. There are actually 4 V’s of big data (Volume, Velocity, Variety and Veracity) and we have been enjoying using those v’s as we learned through our information exchanges and partnering with IBM.
The First Two V’s Focus On The Mission Side: Variety And Veracity
Variety refers to how many categories of data does a data set cover. That would include technology (sources, formats (e.g. numeric, text, objects, geocoded, vector, raster, structured, unstructured – email, video, audio, etc.), methods), legal (complexity, privacy, jurisdiction), and other dimensions of data (temporal, geospatial, sentiment, metadata, logs, etc.)
Veracity refers to our understanding of the data authority to include data quality, data type, and data management maturity so that the user can understand how much to trust that the data is correct, complete, and accurate.
The Other V’s Focus On The Speed And Amount: Velocity And Volume
Volume refers to how much data we are processing, to include data capture, processing, reporting, and managing a large volume of data.
Velocity refers to how often the data changes or is it in real-time. This attribute usually includes analyzing and exploiting lots of new data in real-time.
Changes To The V’s Over The Last 15 Years
Veracity is the newer “V” of the 4 “V’s”. The concept of data veracity, or data quality, has always been the “orphaned step-child” of the 4 “V’s”. It is the “I” in “IT”. It is the part of the iceberg under the water. All IT vendors want to sell speed, and handle lots of data. However, once that is all sold by the vendor you are on your own. That is unless you want to spend $300/hour for mission customization. This is one of the many reasons why Xentity focuses on data…we want to bring the focus back to a very ignored subject in IT.
As of late, value has been introduced to the topic of Big Data as well. Paraphrasing the spanish article referenced here, even if you can produce information if there is no real action that can be done with it then it is not valuable to the organization.
Then again, some have accused IBM of stealing the V’s from 2001 Gartner V’s development . This V-gate controversy:
If anything, these articles prove that the 4 V’s in Big Data is a concept that is worth researching. It is also worth digging into once you see it has its merits.