The INFOMIX system for advanced integration of incomplete and inconsistent data

The Small&Medium steel enterprises is relatively weak on information technology, and the information management personnel lack the urgent need for information integration. According to the actual needs of the Small&Medium steel enterprises information management, three-tier architecture of information integration systems is proposed in this paper. By using SQL Server to implement database and data warehouse, data mining models is built and the design of information integration system is completed. The system covers the steel purchase, inventory, sale, distribution, contracts, finance, statistical analysis, decision support and other management functions. The proposed system can meet the Small&Medium steel enterprises scientific and orderly management for information resources, and the needs of managers forecasting, decision-making. Data warehouse and data mining applications can give an excellent support to the implementation of business intelligence in the future.

Many data driven organisations need to integrate data from multiple, distributed and heterogeneous resources for advanced data analysis. A data integration system is an essential component to collect data into a data warehouse or other data analytics systems. There are various alternatives of data integration systems which are created in-house or provided by vendors. Hence, it is necessary for an organisation to compare and benchmark them when choosing a suitable one to meet its requirements. Recently, the TPC-DI is proposed as the first industrial benchmark for evaluating data integration systems. When using this benchmark, we find some typical data quality problems in the TPC-DI data source such as multi-meaning attributes and inconsistent data schemas, which could delay or even fail the data integration process. This paper explains processes of this benchmark and summarises typical data quality problems identified in the TPC-DI data source. Furthermore, in order to prevent data quality problems and proactively manage data quality, we propose a set of practical guidelines for researchers and practitioners to conduct data quality management when using the TPC-DI benchmark.

The task of combining data residing at different sources to provide the user a unified view is known as data integration. Schema mappings act as glue between the global schema and the source schemas of a data integration system. Global-and-local-as-view (GLAV) is one the approaches for specifying the schema mappings. Tableaux are used for expressing queries and functional dependencies on a single database. We investigate a general technique for expressing a GLAV mapping by a tabular structure called mapping assertion tableaux (MAT). In a similar way, we also express the tuple generating dependency (tgd) and equality generating dependency (egd) constraints by tabular forms, called tabular tgd (TTGD) and tabular egd (TEGD), respectively. A set consisting of the MATs, TTGDs and TEGDs are called schema mapping tableaux (SMT). We present algorithms that use SMT as operator on an instance of the source schema to produce an instance of the target schema. We show that the target instances computed by the SMT are `minimal' and `most general' in nature. We also define the notion of equivalence between the schema mappings of two data integration systems and present algorithms that optimize schema mappings through the manipulation of the SMT.

The thesis reports of a study into the effect upon organisations of co-operative information systems (CIS) incorporating flexible communications, group support and group working technologies. A review of the literature leads to the development of a model of effect based upon co-operative business tasks. CIS have the potential to change how co-operative business tasks are carried out and their principal effect (or performance) may therefore be evaluated by determining to what extent they are being employed to perform these tasks. A significant feature of CIS use identified is the extent to which they may be designed to fulfil particular tasks, or by contrast, may be applied creatively by users in an emergent fashion to perform tasks. A research instrument is developed using a survey questionnaire to elicit users judgements of the extent to which a CIS is employed to fulfil a range of co-operative tasks. This research instrument is applied to a longitudinal study of Novell GroupWise introduction at Northamptonshire County Council during which qualitative as well as quantitative data were gathered. A method of analysis of questionnaire results using principles from fuzzy mathematics and artificial intelligence is developed and demonstrated. Conclusions from the longitudinal study include the importance of early experiences in setting patterns for use for CIS, the persistence of patterns of use over time and the dominance of designed usage of the technology over emergent use.

This study aims to explain the relationship between information system (IS) integration and hospital efficiency, measured in two years, 1997 and 1998. The study used 349 urban hospitals in the analysis. The hospitals' IS integration strategy was measured by multiple indicators of the software system applications and IS resources used in 1997. Hospital performance was measured by the levels of efficiency, using technical efficiency scores computed by Data Envelopment Analysis (DEA) for 1997 and 1998. The DEA analysis shows that, among the urban hospitals studied, the number of efficient hospitals increased during the period 1997-1998. It was found that information system integration is statistically significantly associated with the DEA technical efficiency scores in 1997 and 1998. However, system integration is negatively associated with the 1997 efficiency score and changed to a positive direction in 1998. Hospitals that deployed a highly integrated IS strategy did not show an immediate benefit. However, the IS integration strategy enhanced hospitals' technical efficiency in the next year.

This paper develops a knowledge-based model of information systems (IS) integration in acquisition-based growth programs. Previous research has found important differences in the acquirers’ abilities for acquisition IS integration, and that these differences play key roles in explaining the economic benefits of acquisition-based growth. A knowledge-based view of acquisition IS integration contributes explanation to how differences in abilities arise. Our knowledge-based model is developed by an analytic induction approach, comprising both deductive and inductive analysis of the industry group Trelleborg. The analyses yield five propositions that explain the building of knowledge for acquisition IS integration by the mechanisms of routine refinement, superstitious learning, expertise building, sub-activity refinement and related expertise building. Together, the five propositions form a knowledge-based model of acquisition IS integration. The model suggests that ‘serial acquirers’ form the knowledge necessary for attending to an IS integration challenge over a series of heterogeneous acquisitions. Differences in acquirers’ abilities for acquisition IS integration that depend on knowledge variations are therefore persistent and hard to overcome for the inexperienced acquirer.

Experiences using DIKE, a system for supporting cooperative information system and data warehouse design

Competitive Intelligence (CI) is the process of managing information emanating from the business environment of an organization in order to support decision making process. CI enables the development of strategies that confer companies a significant competitive advantage. The appropriate decisions are taken when all required data are considered. As the amount of data grows very fast inside and outside of an enterprise, exploiting these mountains of data efficiently became a crucial need. Note that such data are usually multiples, heterogeneous, autonomous and distributed. The main issue is related to the identification and resolution of structural and semantic heterogeneity between data, usually spread in multiple sources. Data integration is a significant solution that addresses these problems. Data Warehouse (DW) is viewed as Data Integration System (DIS) that consolidates several data sources in the same target repository through an Extract-Transform-Load (ETL) process. In a decisional context, DW is a relevant solution to aggregate a huge amount of data and organizing them in order to facilitate their analysis and support decision making. In this paper, we propose an approach for designing Semantic Data Warehouse (SDW) to support CI process. Our proposal takes as inputs decision makers' requirements and a set of Semantic Databases (SDB) sources for building the SDW.

Cooperative information system (CIS) is a complex system that involves the cooperation of several stakeholders sharing a common purpose, with different viewpoint on the system. This makes its development more difficult. The successful design of a CIS is then mainly based on the definition of the requirements engineering phase. In software engineering domain, especially in requirements engineering domain, Viewpoint and abstraction level are two important concepts introduced to reduce systems complexity. In this paper, we present an approach oriented viewpoints/abstraction levels which defines the necessary concepts to elicit the requirements of a CIS. In doing so, a model driven method is proposed to develop a CIS modelling tool. In this method, we proposed first a meta-model oriented viewpoints/abstraction levels which decomposes a CIS according to its different viewpoints. We then proposed a modelling tool, viewpoints for cooperative information system (VpCIS) generated from the meta-model.

Repositories for co-operative information systems

Data warehousing is an emerging technology that greatly extends the capabilities of relational databases specifically in the analysis of very large sets of time-oriented data. The emergence of data warehousing has been somewhat eclipsed over the past decade by the simultaneous emergence of Web technologies. However, Web technologies and data warehousing have some natural synergies that are not immediately obvious. First, Web technologies make data warehouse data more easily available to a much wider variety of users. Second, data warehouse technologies can be used to analyze traffic to a Web site in order to gain a much better understanding of the visitors to the Web site. It is this second synergy that is the focus of this article.

PurposeThe purpose of this paper is to understand the relationship between information systems (IS) integration and business performance in the context of the ad traffic system of a media company.Design/methodology/approachA system dynamics (SD) model that shows ad traffic system structure was developed and simulation scenarios were examined.FindingsSimulation scenarios identify the dysfunctional effects of the lack of IS integration. The model shows how IS integration problems increase the dynamic complexity of business processes, resulting in poor business performance. It also shows how and why IS integration improvements can lead to superior performance.Research limitations/implicationsResearchers of business process management will benefit from a wider adoption of simulation and SD modeling approaches. The modeling process and model validation are discussed.Practical implicationsSD modeling can help organizations analyze and streamline their business processes through IT, significantly and sustainably improving their business performance.Originality/valueModeling the relationship between IS integration and business performance through time.

In this paper author presents an experiment, which shows that it is possible to form a federation of data warehouses that may simulate effectively one, “super” data warehouse. There is no need to create complete ETL tool to load data from source data warehouses into one, dedicated data warehouse. Good relations between global schema and local schemas extracted during schema integration are indispensable to create an effective federation.

Since the mid‐1980s, the subject of information systems (IS) integration and its role in business process improvement (BPI) has been of considerable interest to business managers and researchers. The present study examines the effects of IS integration on BPI. The moderating effects of industry type, information intensity of the industry, and time since the initiation of the existing program in the firm have also been analyzed. The data for the study were gathered through a survey of Fortune 500 US firms at divisional levels. The results of the study support the hypotheses that data integration and communication networks integration affect the dimensions of BPI. However, none of the moderators, except industry type, was found significantly affecting the relationships between networks integration and process improvement effect and customer focus.

In this research, earlier developed information integration method and novel web technologies are applied to intensify infrastructure construction process control. The applied method uses semantic methods to integrate scattered information that is later on exploited by process management using state-of-the-art web technologies. The applied method and web technologies not only improve the process management situation awareness by integrated up-todate multi-source process data but also provide platform independent access and visualization tool for process data. Utilization of such technologies potentially lead on cost savings, make processes safer and also more environmentally friendly. The integration method also enables intelligent queries to the integrated data making possible to use machine based inferring to the data.