Evolvable Systems for Big Data Management in Business
This tackles the problem of long-term adaptability and interoperability in Big Data systems for businesses, though it appears incremental as it builds on existing software solutions.
The paper addresses the challenge of designing Big Data systems that must adapt to evolving technologies and requirements over extended periods, presenting CRISTAL-ISE software that enables dynamic system evolution and interoperability, which has been commercialized as Agilium-NG BPM.
Big Data systems are increasingly having to be longer lasting, enterprise-wide and interoperable with other (legacy or new) systems. Furthermore many organizations operate in an external environment which dictates change at an unforeseeable rate and requires evolution in system requirements. In these cases system development does not have a definitive end point, rather it continues in a mutually constitutive cycle with the organization and its requirements. Also when the period of design is of such duration that the technology may well evolve or when the required technology is not mature at the outset, then the design process becomes considerably more difficult. Not only that but if the system must inter-operate with other systems then the design process becomes considerably more difficult. Ideally in these circumstances the design must also be able to evolve in order to react to changing technologies and requirements and to ensure traceability between the design and the evolving system specification. In other words extended design periods necessitate adaptable design specifications. For interoperability Big Data systems need to be discoverable and to work with information about other systems with which they need to cooperate over time. We have developed software called CRISTAL-ISE that enables dynamic system evolution and interoperability for Big Data systems, it has been commercialised as the Agilium-NG BPM product and is described in this paper.