Big Data Usage
The continuing integration of digital services (Internet of Services), smart, digital products (Internet of Things) and production environments (Internet of Things, Industry 4.0) includes the usage of big data in most integration steps. A recent study by General Electric examined the various dimensions of integration within the airline industry (Evans 2012). Smart products like a turbine are integrated into larger machines, in the first example this is an airplane. Planes are in turn part of whole fleets that operate in a complex network of airports, maintenance hangars, etc. At each step, the current integration of the business processes is extended by big data integration. The benefits for optimisation can be harvested at each level (assets, facility, fleets, and the entire network) and by integrating knowledge from data across all steps.
The infrastructure within which Big Data Usage will be applied will adapt to this integration tendency. Hardware and Software will be offered as services, all integrated to support Big Data Usage. See the figure below for a concrete picture of the stack of services that will provide the environment for “Beyond technical standards and protocols, new platforms that enable firms to build specific applications upon a shared framework/architecture [are necessary]”, as foreseen by the GE study or the “There is also a need for on-going innovation in technologies and techniques that will help individuals and organisations to integrate, analyse, visualise, and consume the growing torrent of big data”, as sketched by McKinsey’s study (Manyika et al 2011).
The Figure below shows big data as part of a virtualised service infrastructure. At the bottom level, current hardware infrastructure will be virtualised with cloud computing technologies; hardware infrastructure as well as platforms will be provided as services. On top of this cloud-based infrastructure, Software as a Service (SaaS), and on top of this Business Processes as a Service (BPaaS) can be built. In parallel, big data will be offered as a service and embedded as the precondition for Knowledge services, e.g., the integration of Semantic Technologies for analysis of unstructured and aggregated data. Note that Big Data as a Service may be seen as extending a layer between PaaS and SaaS.
This virtualisation chain from hardware to software to information and knowledge also identifies the skills needed to maintain the infrastructure. Knowledge workers or data scientists are needed to run Big Data and Knowledge services.
Excerpt from: Becker, T. (2015) ‘Big Data Usage’, in Cavanillas, J. M., Curry, E., and Wahlster, W. (eds) New Horizons for a Data-Driven Economy: A Roadmap for Usage and Exploitation of Big Data in Europe. Springer Berlin / Heidelberg.
- Peter C. Evans, Marco Annunziata, “Industrial Internet: Pushing the Boundaries of Minds and Machines”, GE, November 26, 2012.
- J. Manyika et al., McKinsey & Company, “Big data: The next frontier for innovation, competition, and productivity”, 2011.