THE ROLE OF DATA ARCHITECTURE AS A PART OF ENTERPRISE ARCHITECTURE

In the early days of computing, technology simply automated manual processes with greater efficiency. The new organizational context provides input into the data architecture and is the primary tool for the management and sharing of enterprise data. It enables architects, data modelers, and stakeholders to identify, classify, and analyze information requirements across the enterprise, allowing the right priorities for data sharing initiatives. Data architecture states how data are persisted, managed, and utilized within an organization. Data architecture is made up of the structure of all corporate data and its relationships to itself and external systems. In far too many situations, the business community has to enlist the assistance of IT to retrieve information due to the community's inconsistency, lack of intuitiveness, or other factors. The goal of any architecture should illustrate how the components of the architecture will fit together and how the system will adapt and evolve over time.data architecture, enterprise architecture, business process planning,databases, business objects.

A look at cloud architecture interoperability through standards

Enabling cloud infrastructures to evolve into a transparent platform while preserving integrity raises interoperability issues. How components are connected needs to be addressed. Interoperability requires standard data models and communication encoding technologies compatible with the existing Internet infrastructure. To reduce vendor lock-in situations, cloud computing must implement universal strategies regarding standards, interoperability and portability. Open standards are of critical importance and need to be embedded into interoperability solutions. Interoperability is determined at the data level as well as the service level. Corresponding modelling standards and integration solutions shall be analysed

SOA, SoBI & EDA - Paradigms for Integration Capabilities of BI Platform

A Business Intelligence (BI) provider may offer a basic solution, a packed application or a comprising BI platform which integrates components from individual technologies in a synergic system. The providers’ tendency is to standardize the instruments offered on a single server platform. The article analyzes the integration capabilities and problems of BI platforms, emphasizes the differences between emergent technologies and suggests integration solutions. The analysis is useful both to the providers of BI solutions - in order to develop some agile platforms, as well as to their users - representing an important factor in selecting the solution. In addition, the conclusions to be drawn will emphasize the tendencies from the BI market and will represent the support in creating some agile platforms.Business Intelligence, agile platform, integration, metadata management, Service Oriented Architecture (SOA), Event Driven Architecture (EDA)

Towards guidelines for building a business case and gathering evidence of software reference architectures in industry

Background: Software reference architectures are becoming widely adopted by organizations that need to support the design and maintenance of software applications of a shared domain. For organizations that plan to adopt this architecture-centric approach, it becomes fundamental to know the return on investment and to understand how software reference architectures are designed, maintained, and used. Unfortunately, there is little evidence-based support to help organizations with these challenges. Methods: We have conducted action research in an industry-academia collaboration between the GESSI research group and everis, a multinational IT consulting firm based in Spain. Results: The results from such collaboration are being packaged in order to create guidelines that could be used in similar contexts as the one of everis. The main result of this paper is the construction of empirically-grounded guidelines that support organizations to decide on the adoption of software reference architectures and to gather evidence to improve RA-related practices. Conclusions: The created guidelines could be used by other organizations outside of our industry-academia collaboration. With this goal in mind, we describe the guidelines in detail for their use.Peer ReviewedPostprint (published version

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings

Exploring knowledge management integration through EAI in local government domain

Information Technology (IT) infrastructure integration and knowledge management share communal objectives e.g. to make organisations more effective and efficient, agile and innovative, and more responsive to market changes. Such association when assimilates bona fide knowledge management philosophy, it offers the IT departments a headship opportunity for organisational transformation in affiliation with the rest of the establishment. Notwithstanding, in the context of Local Government Authorities (LGAs), the non-integrated nature of the IT infrastructure is associated with inefficient data and knowledge exchange and reduction in LGA services’ quality. Therefore, numerous data inconsistencies and redundancies occur that impact LGA services to their citizenry. LGAs have deployed Enterprise Application Integration (EAI) technological solutions to integrate their legacy with new developed Information Systems (IS). Literature indicates that EAI achieves integration at five layers namely: (a) connectivity, (b) transportation, (c) transformation, (d) process integration and (e) knowledge integration. This research adapts a Revised Model for Integration Layers (REAL) and tests through a case study in a local authority. The results indicate that cases leading to data inconsistencies and replication can be prevented by integrating knowledge through EAI