|What will replace "Big Data" as a hot buzzword ?
|Smart Data (76)||29%|
|Big Analytics (73)||28%|
|Linked Data (25)||9.5%|
|Internet of Things (23)||8.8%|
|Power Data (9)||3.4%|
|Good Data (5)||1.9%|
The median answer is 2014 - half of KDnuggets readers think "Big Data" will go out fashion by 2014
|When will Big Data go out of fashion?|
|After 2030 (19)||7.3%|
We have ample data, with all its analytical limitations. What we need is Strong Theory.
How about "Electronic Gold"
Steve, Big Data
Interesting POLL results so far. Why would analytics be BIG? The whole idea is to draw knowledge in an efficient way using concise algorithms. I'd also go for Smart Data in a way although it suggests the data has a consciousness and this is not the place to go into that.
Roberto Battiti, Big Data
"Big Data" has a very USA-like sound to me.
It reminds me of movies about immigrants coming to the USA, enticed by pictures of very big groceries growing in the fields.
More than the size of the data (it is at least thirty years that one knows how to use parallel computing to deal with big data) it is a matter of applying more and more automation, what we call Learning and Intelligent OptimizatioN (LION).
F. Gagliardi, Disappearing Data
I believe that the next buzzword will be "Disappearing Data" or "Disappearing Big Data".
I think it roll off the tongue very easy, and it has immediacy to comunicate the new wave of the cloud computing.
Ismail Parsa, Big data mining
Data mining (be it big or small) has always been and will always be about turning data into information and information into a solution, be it in business, gov't or research setting. We are still struggling to improve our environment, just as the cavemen did, albeit with slightly better tools. The problem will be more or less the same when the machines take over, a trend that has already started in many high-tech companies.
For what it's worth, I'll call the next new thing "big data mining" and the thing after that "autonomous mining". Coming back to where we are now, sadly many commercial/open source big data mining algorithms are still single threaded... This is where and why the industry is still crawling. At this speed, I'd say big data mining will begin running in 2-5 years and autonomous mining very soon after that at a much accelerated pace.
k l, Internet of Things
Please let it be "Internet of Things". I would love to hear people say this before silently shaking their heads and wondering how something so smart can sound so dumb.
Dave, Big Data
I think instead of "Big Data", the term that'll finally catch on is "Data As A Platform" or "Data As A Service."
Ross Bettinger, Big data poll
I believe that "Big Data" will be replaced by "Smart Data" because it has more immediacy and marketing buzz than any of the other phrases. I like "Big Analytics" but it does not roll off the tongue as easily as "Smart Data".
I think that "Big Data"'s legs will weaken in 2014 or thereabouts due to the fabricated need to proclaim the new new thing, regardless of whether the old new thing has exhausted its utility and merits replacement.
C Wang, Big Data or Large Data
The terminology "Big data" should be replaced as "Large data", because we study the large data sets instead of the big numbers.
Narayanasami N, What next to Big Data
Alexander Linden, "Big Data"
I do prefer terminology that describes the purpose of an exercise. Big Data is no purpose, nor does it describe what the objective is. The term "Business Intelligence" was good, exactly of that reason. And it pervails.
I am btw amazed that Big Data was able to pull in so much attraction. Shows how powerful some of the vendors, management consultants, analysts, and marketing folks are...
My favourite term is: Information Engineering - but nevertheless - it has a long way to go :-)
I think we'll go back to "data mining" or "predictive analytics", although I'm still pushing for the stylish "extreme analytics" (XA), ha ha!
Eric King, After Big Data
I think we'll find that 'big data' is simply too encompassing. There will be the desire to again break into the independent practices of storage and analytics.
I believe we'll come up with a term to scale beyond 'data warehousing' for storage and access. And "data mining" along with "predictive modeling / analytics" will sustain as very accurate and fitting terms for that practice.
My next prediction is the very near-term death of "data scientist", for several reasons -- - at least in commercial circles:
1. The vast majority of analysts are not truly "scientists." And I'm not sure that they even aspire to be.
2. "Scientist" carries too much academic stigma to be commercially attractive. People are not failing at analytics because they're not building technically adequate models. They're failing because they're not being effective pragmatic business practitioners: evaluating the environment; communicating effectively with leadership; preparing a solid project definition before throwing data and software together; not translating results in terms that are actionable or understood by leadership, etc. etc.
The experience required to make a "Data Scientist" commercially viable do not align with the standard definition of a 'scientist.' It dilutes the formal discipline and focused practice of a true scientist, and is off target strategically for the broader skills needed to make the practice succeed commercially.
"Data Science" and "Data Scientist" will evaporate faster than the 'millennium bug'! You heard it here. :^}
Nasser Mooman, U. Toronto, Name after Big Data