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Disruptive Technologies in Commodity Trading Markets
Data management has also become a topic and focus
of greater importance in recent years, and many firms
in the space have spent considerable time and bud-
get redefining their data management strategy and
architecture. Analyzing massive data sets, including
“big data” requires the ability to visualize it in order
to make business decisions…so user interface design
and visualization tools have also become significantly
more important. Indeed, this is the second most im-
portant area of disruption seen by the respondents
A ComTechAdvisory Report
over the next 12-24 months (Figure 1) as well as the
second largest area for investment (Figure 2). In fact,
if responses indicating “significant” and “some” im-
pacts are summed, it could be argued that this may
be the most impactful technology according to the
respondents (Figure 1).
Being able to deal with vast amounts of data in near
real-time is also an area in which Machine Learning
(ML) and Artificial Intelligence (AI) are seen as hav-
Figure 2: Investment Plans over the Next 12-24 Months
80%
70%
60%
50%
40%
30%
20%
10%
0%
Cloud/SaaS
Data Mining
Machine
Learning
ing application. ComTech sees AI and ML as having
broad applicability in a number of diverse areas, in-
cluding predictive maintenance, optimized produc-
tion, automated trading, and even in software testing.
In the survey, the respondents found ML/AI and au-
tomated trading to be the third and fourth most im-
portant area of impact in the near future in the indus-
Blockchain
Microservices
Opensource
Virtal Reality
try and the third largest area for investment (Figures
1 & 2).
Distributed ledger technologies, known more com-
monly as blockchain, are perhaps the most talked
about technology at the moment. However, despite
much hype around the technology, most investment
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