 On "Big Data"
The Challenge of Managing Big Data, Steve Goodman talks to Martin Adolph of the ITU
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| Martin Adolph, Programme Coordinator,
International Telecommunication Union (ITU) |
Martin Adolph is a Programme Coordinator at the International Telecommunication Union (ITU), the United Nation’s specialized agency for information and communications technologies (ICT). Working in the Policy and Technology Watch Division of ITU’s standards bureau, Martin is responsible for surveying the ICT environment to capture new topics for standardization activities. Fascinated with innovation and new technologies, he authored Technology Watch reports (http://itu.int/techwatch) on biometrics, cloud computing, gaming, e-learning, sensor networks and other topics. Martin is coordinating ITU-T activities in the area of intelligent transport systems (ITS) and machine-to-machine communications (M2M). Martin holds diplomas in Computer Science from Dresden University of Technology and Engineering from Ecole Centrale Paris.
Q: Between texts, tweets, mobile commerce, GPS, telecom, etc, I have read that it is now something like upwards of 2 quintillion bytes of data being generated daily. What exactly do we mean by “Big Data” and want challenges is it creating?
A: In our upcoming Technology Watch report, Big data – big today, normal tomorrow, we describe Big Data as a composite term describing emerging technological capabilities in solving complex tasks. It has been hailed by industry analysts, business strategists and marketing pros as a new frontier for innovation, competition and productivity. The hype around big data looks set to match the stir created by cloud computing where existing offerings were rebranded as ‘cloud-enabled’ overnight and whole organizations moved to the cloud.
However, putting the buzz aside, big data has transformational capabilities and motivates researchers from fields as diverse as physics, computer science, genomics and economics – where it is seen as an opportunity to invent and investigate new methods and algorithms capable of detecting useful patterns or correlations present in big chunks of data. Analyzing more data in shorter spaces of time can lead to competitive advantage and better, faster decisions in areas spanning finance, health and research.
What’s clear is that global standards are a key missing ingredient, perhaps one of the biggest challenges in terms of global adoption of big data solutions in a wider range of scenarios.
Q: And, it is not only the volume of Big Data that creates challenges, it is its complexity, isn’t that correct? We are dealing with a combination of structured data like banking and ecommerce transactions, and unstructured data such as text and video, and everything else in between, can you elaborate?
A: Much of the growth of data is unstructured data, making it critical for systems to be able to process it efficiently and to correctly determine the meaning contained within it. For example, emails and text messages as well as audio and video streams are some of the largest categories of unstructured data today. This type of unstructured data continues to grow unabated, making the efficient processing of it critical to the continued success of business analytic processing systems.
For more information visit:
www.itu.int
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