What's Big Data?By the term Big Data we mean a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of heterogeneous data by enabling high-velocity capture, discovery and analysis.
ScopeThe OW2 Big Data initiative aims at fostering the growth of a business ecosystem opening new challenges and opportunities to companies, organizations, technology stakeholders, consultants and end-users to obtain competitive advantage in the Big Data and Business Intelligence domains, exploiting opportunities provided by an open approach, including the adoption of OW2 open source code base.
The initiative also aims to:
- design new ways of inquiring, displaying and exploring data, and develop specific tools to be primarily used by data scientists
- make best use of open source assets in the Business Intelligence and Data Management domains
- develop or integrate new Big Data management solutions
- build a specific business-oriented use case catalogue in the big data domain
- encourage the pervasive adoption of practises and standards for open data publication
- investigate techniques for interpretation and real-time analysis of big data streams
- foster sharing of raw data and anonymous data
- create an environment for interdisciplinary competences in joint development projects
- propose OW2 as the platform that integrates and/or stores the results coming from collaborative research and development projects.
BackgroundThe OW2 Big Data initiative is the evolution of the former . The Big Data scenario is not fully explored yet and we are just at the beginning of this process. Big Data doesn't only address current technologies but also the digital economy of the future.
Big Data impact on technology allows data capture, management and analysis, but it also involves all aspects of raw data. This points out two further crucial concepts:
- open data, which helps to enrich the amount of treatable data within organizations,
- revitalization of competences, which have often been sacrificed in the traditional Business Intelligence domain. They include, among others, the figure of the data scientist, who deals with raw data in order to identify value extraction opportunities.