Disruptive Technologies in Commodity Trading Markets A ComTechAdvisory Report
Data , Big Data , and Data Management
Data is everywhere and in almost every format . According to IDC 5 the digital universe is set to reach 180 zettabytes ( 180,000,000,000,000,000,000 , 000 bytes ) by 2025 as data creation and capture accelerates … in fact , more data has been created in the last 20-years than in the whole prior existence of mankind . Unfortunately , much of this data is not contained in structured lists residing in relational databases , but rather is unstructured in the form of photos , videos , social media content , and more . Web-enabled devices , ranging from smart consumer products to sensor-enabled field equipment , are increasingly common and important sources of data , and as the Internet of Things ( IOT ) expands , so too will the amount of data – all of it increasingly in near real-time . And as data and data sources increase in quantity , heightened concerns regarding the security and use of that information are growing as well – resulting in a number of new and emerging regulations around the globe regulating how data is captured , stored and used , including data associated with industrial activities such as commodity trading . That said , many regulations , including Dodd Frank and REMIT / MIFID , have forced increased market transparency across parts of the commodities complex , resulting in increased availability of data to inform decision making .
Highlighting the increased importance of data , Thompson-Reuters 6 reported last year that in a survey of over 700 commodity professionals , more than 60 % of those surveyed expected their firms to increase budgets for data management , driven by a need to cut total cost of ownership , centralize data , reduce operational risk and create an analytics platform to better manage growing complexity in data management .
Data is now the life blood of commerce ; and in commodities , data is the essential ingredient for the tools of decision making and trading , including analytical models , predictive models , and high-frequency trading .
Over the past couple of years , even as CTRM software sales and deployment slowed , ComTech was observing increased market attention and expenditures on data management strategies , including data capture , storage , integration , retrieval and visualization . This increased focus and spend may have contributed to delayed CTRM procurement activity as a coherent architecture and data management strategy is increasingly viewed as a critical precursor to deploying other key solutions such as CTRM software . Driven in large part by the increased market awareness of the criticality of data management tools , we have seen increasing M & A activity in the data management space for energy and commodities . For example , Drillinginfo has , within the last couple of years , acquired a number of data-centric firms , including Datagenic ,
5 https :// www . forbes . com / sites / michaelkanellos / 2016 / 03 / 03 / 152000-smart-devices-every-minute-in-2025-idc-outlines-the-future-of-smart-things /# 61b8236d4b63
6 https :// blogs . thomsonreuters . com / financial-risk / trading / drilling-for-data-gold-who-has-the-tools-for-commodities-success / © Commodity Technology Advisory LLC , 2018 , All Rights Reserved .
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