How many Vs do you need to describe Big Data dimensions?
12 years ago Doug Laney listed the 3 dimensions of Data management in a Gartner (then Meta Group) research: Volume, Variety, Velocity.
Nowadays, the evolution of Data Management also refers to Big Data. In order to describe it, Gartner added a C to the 3Vs: Volume, Variety, Velocity, Complexity.
Forrester added Variability. Is Variability like Complexity?
Recently, Gartner has introduced 12 dimensions for Big Data grouped into three tiers.
[The debate is still open: here you can find one more contribution.]
First question is: Does Vs make sense? Do we need Vs?
By rephrasing this post I can say that “IT industry simply loves acronyms … As acronyms go, Vs isn’t as bad as it could be. If they help do describe the big data problem, let’s go with Vs.”
Briefly, now we have 5 Vs: Volume, Variety, Velocity, Variability (and/or Complexity) and Value:
- Volume: large amount of data
- Variety: different data formats
- Velocity: continuous data streams and record creation
- Variability and/or Complexity: different meanings and complexity of data types
- Value: extract meaning from information.
Value is the key V. You may argue it’s not a big data dimension, but Value refers to the reason for using big data. It refers to the business case.
What’s the business case? This is the first point outlined by Forrester’s Boris Evelson when asking the key questions on big data
In the already cited post by Stephen Swoyer , you can find the following quote, confirming that Value is the missing V to the classical Vs: “Big data is a lot more interesting when you bring in ‘V’ for value. Does new data enable an organization to get more value, and are we doing enough to get to that value quickly?”
To address the big data issue, IT Industry must handle business cases and business data coming from users’ needs, as well as give the right results and proper solutions by managing the various big data dimensions.
Value: extract semantic meaning from data providing more business value through a cost-effective process.
This is SpagoBI’s approach to Big Data: have a look at this presentation. SpagoBI is currently working on big data implementation. Next presentation at OW2 Conference, Solutions Linux 2013, Paris. Stay tuned!