Database Systems Journal

ISSN 2069 - 3230

The journal is published under the sponsorship of
The Bucharest University of Economic Studies
and it is produced by the university's own publishing division,
The Bucharest University of Economic Studies Publishing House

Database Systems Journal, Vol. II, Issue 1/2011
Issue Topic: Database Design and Modeling

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1. Building a Spatial Database for Romanian Archaeological Sites (p. 3-12)
Aura-Mihaela MOCANU, University of Economic Studies, Bucharest, Romania
Manole VELICANU, University of Economic Studies, Bucharest, Romania
Spatial databases are a new technology in the database systems which allow storing, retrieving and maintaining geospatial data. This paper describes the steps which we have followed to model, design and develop a spatial database for Romanian archaeological sites and their assemblies. The system analysis was made using the well known Entity-Relationship model; the system design included the conceptual, the external and the internal schemas design, and the system development meant developing the needed database objects and programs. The designed database allows users to load vector geospatial data about the archaeological sites in two distinct spatial reference systems WGS84 and STEREO70, temporal data about the historical periods and cultures, other descriptive data and documents as references to the archaeological objects.
Keywords: Spatial databases, entity-relationship model, conceptual schema, external schema.
2. Conceptual and Statistical Issues Regarding the Probability of Default and Modeling Default Risk (p. 13-22)
Emilia TITAN, University of Economic Studies, Romania
Adela Ioana TUDOR, University of Economic Studies, Romania
In today’s rapidly evolving financial markets, risk management offers different techniques in order to implement an efficient system against market risk. Probability of default (PD) is an essential part of business intelligence and customer relation management systems in the financial institutions. Recent studies indicates that underestimating this important component, and also the loss given default (LGD), might threaten the stability and smooth running of the financial markets. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default is more valuable than the standard binary classification: credible or non credible clients. The Basle II Accord recognizes the methods of reducing credit risk and also PD and LGD as important components of advanced Internal Rating Based (IRB) approach.
Keywords: Probability of default, stress test, PD buckets, pooled PDs, predictive analytics, data mining techniques, statistical methods, loss given default.
3. Modelling Financial-Accounting Decisions by Means of OLAP Tools (p. 23-32)
Diana Elena CODREANU, "Constantin Brancoveanu" University, Romania
At present, one can say that a company’s good running largely depends on the information quantity and quality it relies on when making decisions. The information needed to underlie decisions and be obtained due to the existence of a high-performing information system which makes it possible for the data to be shown quickly, synthetically and truly, also providing the opportunity for complex analyses and predictions. In such circumstances, computerized accounting systems, too, have grown their complexity by means of data analyzing information solutions such as OLAP and Data Mining which help perform a multidimensional analysis of financial-accounting data, potential frauds can be detected and data hidden information can be revealed, trends for certain indicators can be set up, therefore ensuring useful information to a company’s decision making.
Keywords: Analytic proces, data warehousing, databases, decision support systems, OLAP cubes.
4. Modeling Spatial Data within Object Relational-Databases (p. 33-42)
Iuliana BOTHA, University of Economic Studies, Bucharest, Romania
Anda VELICANU, University of Economic Studies, Bucharest, Romania
Adela BARA, University of Economic Studies, Bucharest, Romania
Spatial data can refer to elements that help place a certain object in a certain area. These elements are latitude, longitude, points, geometric figures represented by points, etc. However, when translating these elements into data that can be stored in a computer, it all comes down to numbers. The interesting part that requires attention is how to memorize them in order to obtain fast and various spatial queries. This part is where the DBMS (Data Base Management System) that contains the database acts in. In this paper, we analyzed and compared two object-relational DBMS that work with spatial data: Oracle and PostgreSQL.
Keywords: Database, object-relational database, spatial data, GIS (Geographic Information System), spatial index.
5. Agile Development for Service Oriented Business Intelligence Solutions (p. 43-56)
Marinela MIRCEA, University of Economic Studies, Bucharest, Romania
Anca Ioana ANDREESCU, University of Economic Studies, Bucharest, Romania
Considering the evolution of information and communications technology, the necessity of alignment of public and private sectors to European Union requirements, the current economic crisis, and the global context, all organizations are trying to achieve major changes that would enable them to operate as intelligent organizations. For this purpose, agility and Business Intelligence are seen by most managers as a way to transform their organizations into intelligent organizations. The study highlights the importance of modern approaches (Service Oriented Architecture, Business Process Management, Business Rules, Cloud Computing, Master Data Management) in developing agile Business Intelligence solutions. The paper also presents the stages of developing an agile Business Intelligence solution in the case of public procurement.
Keywords: Business Intelligence, agile development, service oriented architecture, business process management, business rules, public procurement.
6. Proposing a Data Model for the Representation of Real Time Road Traffic Flow (p. 57-64)
Alex Alexandru SIROMASCENKO, University of Economic Studies, Bucharest, Romania
Given recent developments in the fields of GIS data modelling, spatial data representation and storage in spatial databases, together with wireless Internet communications, it is becoming more obvious that the requirements for developing a real time road traffic information system are being met. This paper focuses on building a data model for traffic representation with support from the current free GIS resources, open source technologies and spatial databases. Community-created GIS maps can be used for easily populating an infrastructure model with accurate data; the spatial search features of relational databases can be used to map a given GPS position to the previously created network; open source ORM packages can be employed in mediating live traffic feeds into the model. A testing mechanism will be devised in order to verify the feasibility of the solution, considering performance.
Keywords: Data model, GIS, spatial database, open source technologies.