An Evaluation of Open Source Unit Testing Tools Suitable for Data Warehouse Testing

Verification and validation are two important processes in the software system lifecycle. Despite the importance of these processes, a recent survey has shown that testing of data warehouse systems is currently neglected. The survey participants named besides others modest budget and the lack of appropriate tools as potential reasons for this circumstance. In order to verify these reasons, the paper at hand presents an evaluation of unit testing tools suitable for data warehouse testing. To address the modest budget problem, the range of evaluation candidates is limited to no charge, open source solutions, namely AnyDbTest, BI.Quality, DbFit, DbUnit, NDbUnit, SQLUnit, TSQLUnit, and utPLSQL. The evaluation follows the IEEE 14102-2010 guidelines for evaluation and selection of computeraided software engineering tools in order to guarantee benefits from a practioners’ as well as scientific point of view. It results in a detailed overview of how the testing tools meet criteria such as different testing functionalities. At least one tool, namely DbFit, can be identified as a promising candidate with regard to the requirements

A cross-sector analysis of human and organisational factors in the deployment of data-driven predictive maintenance

Domains such as utilities, power generation, manufacturing and transport are increasingly turning to data-driven tools for management and maintenance of key assets. Whole ecosystems of sensors and analytical tools can provide complex, predictive views of network asset performance. Much research in this area has looked at the technology to provide both sensing and analysis tools. The reality in the field, however, is that the deployment of these technologies can be problematic due to user issues, such as interpretation of data or embedding within processes, and organisational issues, such as business change to gain value from asset analysis. 13 experts from the field of remote condition monitoring, asset management and predictive analytics across multiple sectors were interviewed to ascertain their experience of supplying data-driven applications. The results of these interviews are summarised as a framework based on a predictive maintenance project lifecycle covering project motivations and conception, design and development, and operation. These results identified critical themes for success around having a target or decision-led, rather than data-led, approach to design; long-term resourcing of the deployment; the complexity of supply chains to provide data-driven solutions and the need to maintain knowledge across the supply chain; the importance of fostering technical competency in end-user organisations; and the importance of a maintenance-driven strategy in the deployment of data-driven asset management. Emerging from these themes are recommendations related to culture, delivery process, resourcing, supply chain collaboration and industry-wide cooperation

Doctoral Students' Educational Needs in Research Data Management: Perceived Importance and Current Competencies

Sound research data management (RDM) competencies are elementary tools used by researchers to ensure integrated, reliable, and re-usable data, and to produce high quality research results. In this study, 35 doctoral students and faculty members were asked to self-rate or rate doctoral students’ current RDM competencies and rate the importance of these competencies. Structured interviews were conducted, using close-ended and open-ended questions, covering research data lifecycle phases such as collection, storing, organization, documentation, processing, analysis, preservation, and data sharing. The quantitative analysis of the respondents’ answers indicated a wide gap between doctoral students’ rated/self-rated current competencies and the rated importance of these competencies. In conclusion, two major educational needs were identified in the qualitative analysis of the interviews: to improve and standardize data management planning, including awareness of the intellectual property and agreements issues affecting data processing and sharing; and to improve and standardize data documenting and describing, not only for the researcher themself but especially for data preservation, sharing, and re-using. Hence the study informs the development of RDM education for doctoral students

Practitioner requirements for integrated Knowledge-Based Engineering in Product Lifecycle Management.

The effective management of knowledge as capital is considered essential to the success of engineering product/service systems. As Knowledge Management (KM) and Product Lifecycle Management (PLM) practice gain industrial adoption, the question of functional overlaps between both the approaches becomes evident. This article explores the interoperability between PLM and Knowledge-Based Engineering (KBE) as a strategy for engineering KM. The opinion of key KBE/PLM practitioners are systematically captured and analysed. A set of ranked business functionalities to be fulfiled by the KBE/PLM systems integration is elicited. The article provides insights for the researchers and the practitioners playing both the user and development roles on the future needs for knowledge systems based on PLM

Principles for aerospace manufacturing engineering in integrated new product introduction

This article investigates the value-adding practices of Manufacturing Engineering for integrated New Product Introduction. A model representing how current practices align to support lean integration in Manufacturing Engineering has been defined. The results are used to identify a novel set of guiding principles for integrated Manufacturing Engineering. These are as follows: (1) use a data-driven process, (2) build from core capabilities, (3) develop the standard, (4) deliver through responsive processes and (5) align cross-functional and customer requirements. The investigation used a mixed-method approach. This comprises case studies to identify current practice and a survey to understand implementation in a sample of component development projects within a major aerospace manufacturer. The research contribution is an illustration of aerospace Manufacturing Engineering practices for New Product Introduction. The conclusions will be used to indicate new priorities for New Product Introduction and the cross-functional interactions to support flawless and innovative New Product Introduction. The final principles have been validated through a series of consultations with experts in the sponsoring company to ensure that correct and relevant content has been defined

A model to assess customer alignment through customer experience concepts

Business and Information Technology Alignment (BITA) has been one of the main concerns of IT and Business executives and directors due to its importance to overall company performance, especially today in the age of digital transformation. For BITA has been developed several models which in general has focused in the implementation of alignment strategies for the internal operation of the organizations and in the measurement of this internal alignment, but, there is still a big gap in measurement models of the alignment with the external environment of the organizations. In this paper is presented the design and application of a maturity measurement model for BITA with the customers, where the customers are actors of the external environment of the companies. The proposed model involves evaluation criteria and business practices which the companies ideally do for improve the relationship with their customers.Comment: 12 pages, Preprint version, BIS 2019 International Workshops, Seville, Spain, June 26 to 28, 2019, Revised Paper

Conceptualising the impact of information asymmetry on through-life cost: case study of machine tools sector

Information asymmetry (IA) in terms of contextual variety and importance is one of the most challenging aspects of through-life costing in product-service systems (PSS). IA is an imbalance in the information, data and knowledge shared among the parties involved in a contractual agreement. In manufacturing systems under PSS, interaction and effective communication among several parties who are involved in a contractual agreement, rely on the continuity and accuracy of information and context. In such systems, contextual variety exhibits complexity and uncertainty in through-life costing and subsequently in PSS cost assessment. Although the economic aspect of PSS has been studied previously, the impact of IA on through-life cost and for different PSS solutions has not been detailed. Considering manufacturing value chains, this paper introduces a new concept of PSS-hierarchy to perform through-life costing in the presence of IA for various PSS solutions. Moreover, this paper proposes a generic life-cycle model for different PSS solutions to assess the total cost of ownership (TCO). The proposed model has been developed to support decisions on contract design in manufacturing systems. This study considers the manufacturer, service provider and customer perspectives to develop the TCO model using a machine tool manufacturing case study