A few days back Gartner published Hype Cycle for Big Data,2012 and Hype Cycle for Cloud Computing,2012. We reviewed them and compared it with 2011 report and here are a few key new
take-away from the 2012 Gartner reports.
The good news which had been expected by research followers
is that Big Data has moved from ‘On the Rise’ to ‘At the Peak’.
However,
the report goes on to add that Big Data will probably soon move into the Trough of
Disillusionment in 2012 where it will mature in terms of offerings, solutions
and technology maturity. This was stated
in its Hype Cycle for Cloud Computing, 2011 report also but seems Gartner is now
more upbeat about technology players because it goes on to add “However, big
data should spend very little time in the trough”.
The Hype Cycle
for Cloud Computing, 2012 report also states that there will be attempts to combine MapReduce
with Graph as well as natural-language processing and text analytics. Refer one
of our articles on Facebook’s one such attempt among its many successful use cases.
The slight
worrisome statement from the report is that “big data assets, such as images,
video, sound and even three-dimensional object modeling, will also drive big
data into the trough”. We know a lot of research is already happening on this
and have in this site tried to cover one such architectural solution for Hadoop usage in video, sound search and modeling.
As in many other
technology product life cycles, Gartner predicts that specialized technologies
could become mainstream while newer technologies will emerge as the next major
big data issue surfaces up.
In the Hype Cycle
for Big Data, 2012, Gartner attributes one of the major reasons for increased
focus on Big Data to “increased availability of scalable, elastic resources in the cloud have
allowed organizations to begin big data projects without investing in
infrastructure.”
It further details
out 3 categories:
Entries that describe enabling
technologies for big data
-
among the others, the one to note is column-store DBMS.
o
Refer our post on one such solution which uses column-store DBMS for higher performance
Entries that describe typical
use cases for big data
-
among the other, the one catching attention is telematics
Entries that describe new
information types, sources and roles
-
on expected lines, we know Data Scientist should feature
here
For complete text,
you may refer the 2012 reports at the links given above.
Going a step
further, we have applied Map Reduce on Hype Cycle for Big Data, 2012 report. We
took all statements where Sample Vendors were suggested by Gartner in the
technologies shown in Hype Cycle image at top. Our algorithm returned a count
on how many times a vendor has been suggested in the report. The image below
shows a graph generated by the data from MapReduce algorithm to
arrive at a vendor mention count. (click on image to view full image).
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