THE DECISION SUPPORT SYSTEMS FOR THE INFORMATION SOCIETY (i-Society)

The globalization process needs exact information flows that should be collected in due time. The Information Society ensures the communication between people with different expertise from various geographical areas that have similar interests. The increase of the companies’ activities leads implicitly to the increase of the volume and the complexities of databases, as well as the continuous modernization of the integrated information systems in order to collect the information in due time, that is requested by the decision takers and the frequent use of DSS. The paper presents the DSS structure, the main facilities offered by the associated software products, an evolution of the databases technologies, as well as a list of the program products used to process the statistical data and data mining in order to obtain the main sources of information that is necessary to take decisions.Information Society (i-Society); Data Base; Information Systems; Decision Support Systems (DSS); Statistical Package, Portal technology

An Open Source Based Data Warehouse Architecture to Support Decision Making in the Tourism Sector

In this paper an alternative Tourism oriented Data Warehousing architecture is proposed which makes use of the most recent free and open source technologies like Java, Postgresql and XML. Such architecture's aim will be to support the decision making process and giving an integrated view of the whole Tourism reality in an established context (local, regional, national, etc.) without requesting big investments for getting the necessary software.Tourism, Data warehousing architecture

Extending Uml for Multidimensional Modeling in Data Warehouse

Multidimensional modeling is the foundation of data warehouses, MD databases, and On-Line Analytical Processing (OLAP) applications. Nowadays Dimensional modeling and object-orientation are becoming growing interest areas. In the past few years; there have been many proposals, for representing the MD properties at the conceptual level. However, none of them has been accepted as a standard for conceptual MD modeling. In this paper, we present an extension of the Unified Modeling Language (UML) using a UML profile for multidimensional databases. This profile is composed of a set of stereotypes, constraints and tagged values. We have extended the uml for representing the main multidimensional properties at the conceptual level such as the many-to-many relationships between facts and dimensions, degenerate dimensions, multiple and alternative path classification hierarchies, and nonstrict and complete hierarchies and aggregate fact table

A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

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)

Database Systems - Present and Future

The database systems have nowadays an increasingly important role in the knowledge-based society, in which computers have penetrated all fields of activity and the Internet tends to develop worldwide. In the current informatics context, the development of the applications with databases is the work of the specialists. Using databases, reach a database from various applications, and also some of related concepts, have become accessible to all categories of IT users. This paper aims to summarize the curricular area regarding the fundamental database systems issues, which are necessary in order to train specialists in economic informatics higher education. The database systems integrate and interfere with several informatics technologies and therefore are more difficult to understand and use. Thus, students should know already a set of minimum, mandatory concepts and their practical implementation: computer systems, programming techniques, programming languages, data structures. The article also presents the actual trends in the evolution of the database systems, in the context of economic informatics.database systems - DBS, database management systems – DBMS, database – DB, programming languages, data models, database design, relational database, object-oriented systems, distributed systems, advanced database systems

Data Mining in Electronic Commerce

Modern business is rushing toward e-commerce. If the transition is done properly, it enables better management, new services, lower transaction costs and better customer relations. Success depends on skilled information technologists, among whom are statisticians. This paper focuses on some of the contributions that statisticians are making to help change the business world, especially through the development and application of data mining methods. This is a very large area, and the topics we cover are chosen to avoid overlap with other papers in this special issue, as well as to respect the limitations of our expertise. Inevitably, electronic commerce has raised and is raising fresh research problems in a very wide range of statistical areas, and we try to emphasize those challenges.Comment: Published at http://dx.doi.org/10.1214/088342306000000204 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org