Security Management of Intelligent Technologies in Business Intelligence Systems

The article discusses the security methods of intelligent technologies in Business Intelligence (BI) systems. Security technologies are considered taking into account BI four-layer architecture which includes: а) transactional systems layer; b) ETL-procedures – extraction, conversions and data loading layer; c) data warehouses and data marts layer; d) OLAP-tools and user interface layer. The characteristic of the general BI systems security technologies, data storage security strategies and intellectual data mining subsystems and OLAP-tools is resulted. For data mining models and to provide them with the analyst, considered the requirements of access rights to the analyzed information, database backups creation necessity, the requirements to hide sensitive data

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

IMPROVING THE QUALITY OF THE DECISION MAKING BY USING BUSINESS INTELLIGENCE SOLUTIONS

On the basis of the decision making stands information, as one of the main elements that determine the evolution of our-days society. As a consequence, data analysis tends to become a priority in the activity of an organization for decision making. The diBusiness Intelligence, Data Warehouse, decision making, SQL Server

On-line analytical processing

On-line analytical processing (OLAP) describes an approach to decision support, which aims to extract knowledge from a data warehouse, or more specifically, from data marts. Its main idea is providing navigation through data to non-expert users, so that they are able to interactively generate ad hoc queries without the intervention of IT professionals. This name was introduced in contrast to on-line transactional processing (OLTP), so that it reflected the different requirements and characteristics between these classes of uses. The concept falls in the area of business intelligence.Peer ReviewedPostprint (author's final draft

Knowledge and Metadata Integration for Warehousing Complex Data

With the ever-growing availability of so-called complex data, especially on the Web, decision-support systems such as data warehouses must store and process data that are not only numerical or symbolic. Warehousing and analyzing such data requires the joint exploitation of metadata and domain-related knowledge, which must thereby be integrated. In this paper, we survey the types of knowledge and metadata that are needed for managing complex data, discuss the issue of knowledge and metadata integration, and propose a CWM-compliant integration solution that we incorporate into an XML complex data warehousing framework we previously designed.Comment: 6th International Conference on Information Systems Technology and its Applications (ISTA 07), Kharkiv : Ukraine (2007

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)

An MDA approach for developing Secure OLAP applications: metamodels and transformations

Decision makers query enterprise information stored in Data Warehouses (DW) by using tools (such as On-Line Analytical Processing (OLAP) tools) which employ specific views or cubes from the corporate DW or Data Marts, based on multidimensional modelling. Since the information managed is critical, security constraints have to be correctly established in order to avoid unauthorized access. In previous work we defined a Model-Driven based approach for developing a secure DW repository by following a relational approach. Nevertheless, it is also important to define security constraints in the metadata layer that connects the DW repository with the OLAP tools; that is, over the same multidimensional structures that end users manage. This paper incorporates a proposal for developing secure OLAP applications within our previous approach: it improves a UML profile for conceptual modelling; it defines a logical metamodel for OLAP applications; and it defines and implements transformations from conceptual to logical models, as well as from logical models to secure implementation in a specific OLAP tool (SQL Server Analysis Services).This research is part of the following projects: SIGMA-CC (TIN2012-36904), GEODAS-BC (TIN2012-37493-C01) and GEODAS-BI (TIN2012-37493-C03) funded by the Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional FEDER. SERENIDAD (PEII11-037-7035) and MOTERO (PEII11- 0399-9449) funded by the Consejería de Educación, Ciencia y Cultura de la Junta de Comunidades de Castilla La Mancha, and Fondo Europeo de Desarrollo Regional FEDER