A Modular Systems Perspective of IT Infrastructure Configurations and Productivity

Research on IT infrastructure investments and organizational productivity has been marked with ambiguity, evidenced by the much debated productivity paradox. Part of the ambiguity arises from a paradigmatic aggregated treatment of IT infrastructure and productivity constructs along with a disregard for contingencies and time lags. The focus in this paper is to extend the component based view to understand IT infrastructure productivity. Using a modular systems perspective, revisiting the constructs in an attempt to disaggregate them for a more detailed examination is proposed. This study adds to the body of knowledge through a holistic examination of the relationship between IT infrastructure configurations, contingencies, and organizational productivity

A Goal and Ontology Based Approach for Generating ETL Process Specifications

Data warehouse (DW) systems development involves several tasks such as defining requirements, designing DW schemas, and specifying data transformation operations. Indeed, the success of DW systems is very much dependent on the proper design of the extracting, transforming, and loading (ETL) processes. However, the common design-related problems in the ETL processes such as defining user requirements and data transformation specifications are far from being resolved. These problems are due to data heterogeneity in data sources, ambiguity of user requirements, and the complexity of data transformation activities. Current approaches have limitations on the reconciliation of DW requirement semantics towards designing the ETL processes. As a result, this has prolonged the process of the ETL processes specifications generation. The semantic framework of DW systems established from this study is used to develop the requirement analysis method for designing the ETL processes (RAMEPs) from the different perspectives of organization, decision-maker, and developer by using goal and ontology approaches. The correctness of RAMEPs approach was validated by using modified and newly developed compliant tools. The RAMEPs was evaluated in three real case studies, i.e., Student Affairs System, Gas Utility System, and Graduate Entrepreneur System. These case studies were used to illustrate how the RAMEPs approach can be implemented for designing and generating the ETL processes specifications. Moreover, the RAMEPs approach was reviewed by the DW experts for assessing the strengths and weaknesses of this method, and the new approach is accepted. The RAMEPs method proves that the ETL processes specifications can be derived from the early phases of DW systems development by using the goal-ontology approach

Creation and management of versions in multiversion data warehouse

ABSTRACT A data warehouse (DW) provides an information for analytical processing, decision making, and data mining tools. On the one hand, the structure and content of a data warehouse reflects a real world, i.e. data stored in a DW come from real production systems. On the other hand, a DW and its tools may be used for predicting trends and simulating a virtual business scenarios. This activity is often called the what-if analysis. Traditional DW systems have static structure of their schemas and relationships between data, and therefore they are not able to support any dynamics in their structure and content. For these purposes, multiversion data warehouses seem to be very promising. In this paper we present a concept and an ongoing implementation of a multiversion data warehouse that is capable of handling changes in the structure of its schema as well as simulating alternative business scenarios

Dynamic Integration of Evolving Distributed Databases using Services

This thesis investigates the integration of many separate existing heterogeneous and distributed databases which, due to organizational changes, must be merged and appear as one database. A solution to some database evolution problems is presented. It presents an Evolution Adaptive Service-Oriented Data Integration Architecture (EA-SODIA) to dynamically integrate heterogeneous and distributed source databases, aiming to minimize the cost of the maintenance caused by database evolution. An algorithm, named Relational Schema Mapping by Views (RSMV), is designed to integrate source databases that are exposed as services into a pre-designed global schema that is in a data integrator service. Instead of producing hard-coded programs, views are built using relational algebra operations to eliminate the heterogeneities among the source databases. More importantly, the definitions of those views are represented and stored in the meta-database with some constraints to test their validity. Consequently, the method, called Evolution Detection, is then able to identify in the meta-database the views affected by evolutions and then modify them automatically. An evaluation is presented using case study. Firstly, it is shown that most types of heterogeneity defined in this thesis can be eliminated by RSMV, except semantic conflict. Secondly, it presents that few manual modification on the system is required as long as the evolutions follow the rules. For only three types of database evolutions, human intervention is required and some existing views are discarded. Thirdly, the computational cost of the automatic modification shows a slow linear growth in the number of source database. Other characteristics addressed include EA-SODIA’ scalability, domain independence, autonomy of source databases, and potential of involving other data sources (e.g.XML). Finally, the descriptive comparison with other data integration approaches is presented. It shows that although other approaches may provide better performance of query processing in some circumstances, the service-oriented architecture provide better autonomy, flexibility and capability of evolution

Where have all the flowers gone?: a modular systems perspective of IT infrastructure design and productivity

Assessing value of IT infrastructure investments has been both difficult and ambiguous. This research develops and tests a conceptual framework to understand the productivity process. A lagged and recursive framework is used to trace the relationship between IT infrastructure investments, infrastructure design, and organizational productivity along with contingencies of IT management and the environment. A major contribution of this study is the use of the systems perspective to disaggregate the concepts of IT infrastructure and productivity into collectively exhaustive types. Findings reveal that IT investments do not significant affect productivity but do so when used to develop an IT infrastructure design. IT management is seen to strongly influence IT infrastructure design. Similarly, organizational environment appears to significantly influence the type of productivity focus for a firm. The study adds to the existing body of knowledge through a holistic investigation of the multi-level relationship between IT infrastructure configurations, contingencies, and productivity

Maintaining Data Warehouses Over Changing Information Sources

This article characterizes the types of dynamicity (such as data updates, schema changes, and constraint modifications) as well as their explicit and implicit generation. This article also identifies issues for data warehousing systems that occur when the possibility of information source changes is taken into consideration. Such issues include adapting wrappers to information source changes, adapting view definitions to changes, or adapting the data content (extent) of the data warehouse. Lastly, possible candidate solutions for some of these problems, especially as explored in the context of the Evolvable View Environment (EVE) system, are outlined. Such flexible data warehousing technology will allow more users to make use of distributed information over networks and increase the productivity of users and system administrators by maintaining customized interfaces to information that can be automatically maintained even under changes of the underlying system

Factors Influencing BI Data Collection Strategies: An Empirical Investigation

The purpose of this dissertation is to examine the external factors that influence an organizations' business intelligence (BI) data collection strategy when mediated by BI attributes. In this dissertation, data warehousing strategies are used as the basis on which to frame the exploration of BI data collection strategies. The attributes include BI insightfulness, BI consistency, and the organizational transformation attribute of BI. The research population consisted of IT professionals and top level managers involved in developing and managing BI. Data was collected from a range of industries and organizations within the United States. An online survey was used to collect the data to empirically test the proposed relationships. Data was analyzed using partial least square path modeling (PLS). The results of this study suggest that there exists a positive relationship between institutional isomorphism and BI consistency. The results also indicate that there exists a positive relationship between BI consistency and BI comprehensive data collection strategy, and the organizational transformation attribute of BI and BI comprehensive data collection strategy. These findings provide a theoretical lens to better understand the motivators and the success factors related to collecting the huge amounts of data required for BI. This study also provides managers with a mental model on which to base decisions about the data required to accomplish their goals for BI

Projecto e implementação de sistemas de Data Warehousing

Nos últimos anos é comum ouvir-se dizer que se está perante a Era da Informação. A massificação das Tecnologias da Informação contribuiu de forma muito significativa para isso. O desenvolvimento impressionante da informática, juntamente com a proliferação generalizada em todos os domínios da computação, e o “nascimento” da Internet foram vitais para que isso acontecesse de facto. O evoluir destas tecnologias afectaram não só os particulares, mas também as empresas, permitindo o acesso via internet a um conjunto muito vasto de informações e a possibilidade de automatizar e processar algumas tarefas até então desempenhadas manualmente. No caso das empresas, o constante desenvolvimento de aplicações informáticas, para o processamento e automatização de tarefas, deu origem ao que agora são denominados de Sistemas Transaccionais. O desenvolvimento deste tipo de sistemas teve também alguma influência no modus operandi das organizações, atingindo um nível de importância tal que a estratégia de negócio de uma empresa é definida não só pelo evoluir do negócio e do mercado, mas também pelo evoluir dos seus Sistemas Transaccionais. No entanto, apesar destes sistemas conterem cada vez mais informação sobre o dia-a-dia da organização, esta poderá estar dispersa por diferentes aplicações, e provavelmente num estado inconsistente, reflectindo assim uma imagem que não será certamente a realidade da organização. Os Sistemas de Data Warehousing surgiram como mais um componente para um Sistema de Informação Empresarial com o objectivo de providenciar uma fonte de dados históricos validados, integrados, “limpos” e não-voláteis, que representem fielmente o estado actual da organização. Estes sistemas foram optimizados para acessos de consulta e permitem aos seus utilizadores a elaboração de relatórios e extracção de conhecimento que servirão de suporte ao processo de tomada de decisões. O projecto, análise e desenvolvimento deste tipo de sistemas requer alguma atenção, em especial nas tarefas inerentes à gestão do projecto, análise de requisitos e definição do âmbito, e no desenvolvimento de ferramentas de extracção, transformação e integração de dados. Existem neste momento na comunidade de data warehousing duas principais abordagens, uma preconizada por William H. Inmon, mais centrada nos dados, e outra por Ralph Kimball, mais centrada no projecto. Ambas as abordagens são bastante válidas, mas a metodologia de Ralph Kimball tem obtido uma maior aceitação por parte do mercado devido à problemática existente na gestão de projectos de data warehousing. A percentagem de projectos de data warehousing que são mal sucedidos é tão elevada que se tem dada grande atenção à questão da gestão do próprio projecto. Assim, não é de surpreender que a metodologia de Ralph Kimball tenha ganho algum relevo nas organizações envolvidas no desenvolvimento de Sistemas de Data Warehousing. Em termos gerais, esta dissertação foi desenvolvida com base num estudo detalhado sobre o planeamento e a implementação de Sistemas de Data Warehousing em organizações reais. Abordaram-se, com particular ênfase, os principais aspectos relacionados com o planeamento, projecto, gestão e integração deste tipo de sistemas em meios empresariais. Complementarmente, e como forma de comprovar a aplicação no mundo real das técnicas de implementação estudadas, realizou-se uma avaliação das práticas correntes seguidas por algumas empresas de relevo no panorama nacional, e empregues no desenvolvimento de projectos de data warehousing.In the last years it is common to hear say that we are in the Age of Information. The widespread use of Information Technologies has contributed significantly to this. The remarkable development of Computer Science, along with the generalized proliferation in all computation domains, and the "birth" of the Internet were fundamental to this achievement. The evolution of these technologies affected significantly current activities of common people and companies, allowing for the access via Internet to large repositories of information, and the possibility to automate activities that were previously done manually. The constant development of software applications to process and automate tasks led to what we know today as Transactional Systems. The development of these systems also had some impact on the organization modus operandi , influenced strongly common business strategies through their own functionalities and services, which were systematically improved during their lifetime. However, despite the fact that these systems gather and store, day after day, more and more information about the organization’s activities, such information may be distributed by different applications, probably in an inconsistent state, reflecting an image that is not the reality of the organization. Data Warehouse Systems emerged as a part of an enterprise information system providing now a new set of computational services that contribute effectively to added value to conventional data processing tasks through their abilities to explore historical, validated, integrated, clean and non-volatile sources of data. These systems were specially optimized for query access and allow their users to make reports and gather subject oriented information that will support business decision making processes. The project, analysis and development of Data Warehousing Systems require some particular attention, especially in tasks such as project management, requisites analysis, scope definition, and in the development of data warehouse populating tools. In the Data Warehousing area there are, essentially, two main approaches, a data-centred one by William H. Inmon, and a project-oriented approach proposed by Ralph Kimball. Both of them are valid approaches. However, the Ralph Kimball’s methodology has gained larger acceptance within the organizations due to its special orientation to the data warehouse project management problems. The percentage of unsuccessful data warehousing projects has been so high that data warehousing experts have been focused a large part of their today’s efforts to project management issues. Thus, it is not a surprise the selection of the Ralph Kimball’s methodology by the organizations that are involved with the project and development of a Data Warehousing System. In general terms, this thesis was developed based on a detailed study that was done about Data Warehousing Systems planning and implementation in real world organizations. Many topics were approached concerning with project design, implementation, management and integration of this systems in enterprise environments. Furthermore, it was performed a particular study about common practices that some relevant companies follow in the national “arena” of data warehousing systems. This study was very useful to prove the application of the implementation techniques and methodologies studied in this thesis to real world data warehousing systems projects