Telecom Italia and the Big Data Challenge 2014 Telecom Italia and the Big Data Challenge 2014

Telecom Italia and the Big Data Challenge 2014

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Telecom Italia, in collaboration with Politecnico di Milano, MIT Media Lab, Trento RISE (with the contribution of Fondazione Bruno Kessler and University of Trento) and EIT ICT Labs, is organizing the "Big Data Challenge" to compete with the feats of Big Data.

Are you an enthusiast, an expert, or do you simply like to be put to the test?

The best ideas will be judged by a panel of experts, with the chance to win major prizes and awards. On 14 January 2014, the Dataset will be released, so you can develop your technologically innovative idea and put yourself to the test.

The three tracks available are:

  1. Development Applications: web based, mobile, or stand-alone applications, developed in any language, provided they use partially or totally the data provided by the contest.
  2. Development Data Analytics: algorithms, methods, statistics automatic or scalable, able to highlight correlations and trends by processing the geo-referenced data provided by the contest.
  3. Development of Data Visualizations: these are static (e.g. infographics) or dynamic and interactive Tracks dedicated to the visual narrative of intelligent data aggregation, through a classic screen or making use of alternative formats.

What is Big Data?

The concept of Big Data came to existence in recent years across Europe, and later in Italy. We often hear of useful applications for the analysis of Big Data, but "non-experts" will certainly have difficulties in understanding exactly what it is.

 What do we mean by the term Big Data?

Let’s start with a definition from the Internet: “Big Data includes datasets  (=collection of data) with sizes beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time ".

It is a set of data that, for its size, cannot be easily "processed", as it requires the creation of ad hoctools and programs.

However, the arrival of Big Data is not just a shift of gear in technological development: every second day, the world produces the same amount of data as produced by mankind since the advent of writing in 2003. This mass information, will over time, increasingly impact the services that citizens enjoy, and therefore changing the way we have been accustomed to finding information, analyzing phenomena, and informing ourselves, etc.…

The advantages

We are moving beyond traditional approaches, which cover a small area of data or a subset of data. As a result of difficulties in collecting or processing such data, it is the only information on which to rely.

Big Data technologies allow us to work with large volume of datasets. This provides a complete vision and removes the phenomena, hence, allowing us to correlate information with no apparent connections.

A common definition of Big Data is characterized by

  • Volume: ability to capture, store and access large volumes of data
  • Speed: ability to perform data analysis in real time (almost)
  • Variety: The data can arrive from different sources

The volume is certainly an important factor, as today we talk about datasets measured in Zettabyte (1 followed by 21 zeros!). But also the speed and the variety with which information is created provide an added impact.

It is the variety of information that will play the pivotal challenge in the Telecom Italia Big Data Challenge, which will offer all participants a dataset with a mix: from telecommunications to transportation, from energy consumption to weather, and so on.

Is it still a little bit 'hazy? Let's practice!

How can Big Data be used concretely?

  • To analyze markets, allowing for a detailed study of the behavior and the evolution of trends, all of which in the past required inputs of time and money. For example, today it is possible toanalyze purchasing behavior via cell phone, to offer the user a particular service in mobility, studying its access via different devices during the day and streamlining the collection of data.
  • To analyze data from disparate sources, so datasets do not require a structure (such as images, e-mail, GPS, information from Social Network). If the data is harmoniously grouped, displayed and connected, it allows to effectively analyze: a phenomenon, a geographic area, or facilitate interventioni (es. Smart Center Telecom Italia).
  • To analyze the conversations related to the social world. For example, you can monitor how the network "speaks" of a phenomenon, by joining the feed of all social channels harmoniously, it allows you to give a glance at the overall trends in order to offer the most lucid analysis, and to monitor sentiment (i.e. the emotional reaction) of the population updates.
  • To analyze the conversations related to the social world. For example, you can monitor how the network "speaks" of a phenomenon, by joining the feed of all social channels harmoniously, it allows you to give a glance at the overall trends in order to offer the most lucid analysis, and to monitor sentiment (i.e. the emotional reaction) of the population updates.
  • For the development of business value, to improve the efficiency and quality of the products or services offered. Today there are sites, for example, which offer content based on the user's previous visits, therefore, identifying their preferences (contextual marketing).