Quality measures for ETL processes: from goals to implementation

Extraction transformation loading (ETL) processes play an increasingly important role for the support of modern business operations. These business processes are centred around artifacts with high variability and diverse lifecycles, which correspond to key business entities. The apparent complexity of these activities has been examined through the prism of business process management, mainly focusing on functional requirements and performance optimization. However, the quality dimension has not yet been thoroughly investigated, and there is a need for a more human-centric approach to bring them closer to business-users requirements. In this paper, we take a first step towards this direction by defining a sound model for ETL process quality characteristics and quantitative measures for each characteristic, based on existing literature. Our model shows dependencies among quality characteristics and can provide the basis for subsequent analysis using goal modeling techniques. We showcase the use of goal modeling for ETL process design through a use case, where we employ the use of a goal model that includes quantitative components (i.e., indicators) for evaluation and analysis of alternative design decisions.Peer ReviewedPostprint (author's final draft

PhyNetLab: An IoT-Based Warehouse Testbed

Future warehouses will be made of modular embedded entities with communication ability and energy aware operation attached to the traditional materials handling and warehousing objects. This advancement is mainly to fulfill the flexibility and scalability needs of the emerging warehouses. However, it leads to a new layer of complexity during development and evaluation of such systems due to the multidisciplinarity in logistics, embedded systems, and wireless communications. Although each discipline provides theoretical approaches and simulations for these tasks, many issues are often discovered in a real deployment of the full system. In this paper we introduce PhyNetLab as a real scale warehouse testbed made of cyber physical objects (PhyNodes) developed for this type of application. The presented platform provides a possibility to check the industrial requirement of an IoT-based warehouse in addition to the typical wireless sensor networks tests. We describe the hardware and software components of the nodes in addition to the overall structure of the testbed. Finally, we will demonstrate the advantages of the testbed by evaluating the performance of the ETSI compliant radio channel access procedure for an IoT warehouse

Building a Data Warehouse step by step

Data warehouses have been developed to answer the increasing demands of quality information required by the top managers and economic analysts of organizations. Their importance in now a day business area is unanimous recognized, being the foundation for developing business intelligence systems. Data warehouses offer support for decision-making process, allowing complex analyses which cannot be properly achieved from operational systems. This paper presents the ways in which a data warehouse may be developed and the stages of building it.data warehouse, data mart, data integration, database management system, OLAP, data mining

Proximal business intelligence on the semantic web

This is the post-print version of this article. The official version can be accessed from the link below - Copyright @ 2010 Springer.Ubiquitous information systems (UBIS) extend current Information System thinking to explicitly differentiate technology between devices and software components with relation to people and process. Adapting business data and management information to support specific user actions in context is an ongoing topic of research. Approaches typically focus on providing mechanisms to improve specific information access and transcoding but not on how the information can be accessed in a mobile, dynamic and ad-hoc manner. Although web ontology has been used to facilitate the loading of data warehouses, less research has been carried out on ontology based mobile reporting. This paper explores how business data can be modeled and accessed using the web ontology language and then re-used to provide the invisibility of pervasive access; uncovering more effective architectural models for adaptive information system strategies of this type. This exploratory work is guided in part by a vision of business intelligence that is highly distributed, mobile and fluid, adapting to sensory understanding of the underlying environment in which it operates. A proof-of concept mobile and ambient data access architecture is developed in order to further test the viability of such an approach. The paper concludes with an ontology engineering framework for systems of this type – named UBIS-ONTO

The Role of Maintenance and Facility Management in Logistics: A Literature Review

Purpose - The purpose of this paper is to provide a literature review on the different ways of carrying out Facility Management and related topics in order to uncover that there is limited research regarding the impact of Facility Management on the logistics and operational performance of warehouses. Design/methodology/approach - Four different focus areas have been identified and for each one different methodologies and streams of research have been studied. Findings - The study underlines the importance of Facility Management for the logistics operations; therefore it supports the notion that investments aiming at preserving the status of the building and service components of warehouses are crucial. Originality/value - This paper aims to suggest to Facility Management managers that they can contribute to enhance business performance by designing effective Facility Management strategie

Showing the Benefits of Applying a Model Driven Architecture for Developing Secure OLAP Applications

Data Warehouses (DW) manage enterprise information that is queried for decision making purposes by using On-Line Analytical Processing (OLAP) tools. The establishment of security constraints in all development stages and operations of the DW is highly important since otherwise, unauthorized users may discover vital business information. The final users of OLAP tools access and analyze the information from the corporate DW by using specific views or cubes based on the multidimensional modelling containing the facts and dimensions (with the corresponding classification hierarchies) that a decision maker or group of decision makers are interested in. Thus, it is important that security constraints will be also established over this metadata layer that connects the DW's repository with the decision makers, that is, directly over the multidimensional structures that final users manage. In doing so, we will not have to define specific security constraints for every particular user, thereby reducing the developing time and costs for secure OLAP applications. In order to achieve this goal, a model driven architecture to automatically develop secure OLAP applications from models has been defined. This paper shows the benefits of this architecture by applying it to a case study in which an OLAP application for an airport DW is automatically developed from models. The architecture is composed of: (1) the secure conceptual modelling by using a UML profile; (2) the secure logical modelling for OLAP applications by using an extension of CWM; (3) the secure implementation into a specific OLAP tool, SQL Server Analysis Services (SSAS); and (4) the transformations needed to automatically generate logical models from conceptual models and the final secure implementation.This research is part of the following projects: SERENIDAD (PEII11- 037-7035) financed by the ”Viceconsejería de Ciencia y Tecnología de la Junta de Comunidades de Castilla-La Mancha” (Spain) and FEDER, and SIGMA-CC (TIN2012-36904) and GEODAS (TIN2012-37493-C03-01) financed by the ”Ministerio de Economía y Competitividad” (Spain)