Application of QVT for the Development of Secure Data Warehouses: A case study

2007 ◽  
Author(s):  
Emilio Soler ◽  
Juan Trujillo ◽  
Eduardo Fernandez-Medina ◽  
Mario Piattini
Keyword(s):  
Data Warehouses ◽  
Secure Data

An MDA Compliant Approach for Designing Secure Data Warehouses

2009 ◽  
pp. 495-503
Author(s):  
Rodolfo Villarroel ◽  
Eduardo Fernández-Medina ◽  
Juan Trujillo ◽  
Mario Piattini
Keyword(s):  
Real World ◽  
Conceptual Modeling ◽  
Security Requirements ◽  
Data Warehouses ◽  
Model Driven ◽  
Secure Data ◽  
Security Information ◽  
Target Platform ◽  
Compliant Approach ◽  
User Security

This chapter presents an approach for designing secure Data Warehouses (DWs) that accomplish the conceptual modeling of secure DWs independently from the target platform where the DW has to be implemented, because our complete approach follows the Model Driven Architecture (MDA) and the Model Driven Security (MDS). In most of real world DW projects, the security aspects are issues that usually rely on the DBMS administrators. We argue that the design of these security aspects should be considered together with the conceptual modeling of DWs from the early stages of a DW project, and being able to attach user security information to the basic structures of a Multidimensional (MD) model. In this way, we would be able to generate this information in a semi or automatic way into a target platform and the final DW will better suits the user security requirements.

An MDA Compliant Approach for Designing Secure Data Warehouses

2011 ◽  
pp. 261-272
Author(s):  
Villarroel Rodolfo ◽  
Fernández-Medina Eduardo ◽  
Trujillo Juan ◽  
Piattini Mario
Keyword(s):  
Real World ◽  
Conceptual Modeling ◽  
Security Requirements ◽  
Data Warehouses ◽  
Model Driven ◽  
Secure Data ◽  
Security Information ◽  
Target Platform ◽  
Compliant Approach ◽  
User Security

This chapter presents an approach for designing secure Data Warehouses (DWs) that accomplish the conceptual modeling of secure DWs independently from the target platform where the DW has to be implemented, because our complete approach follows the Model Driven Architecture (MDA) and the Model Driven Security (MDS). In most of real world DW projects, the security aspects are issues that usually rely on the DBMS administrators. We argue that the design of these security aspects should be considered together with the conceptual modeling of DWs from the early stages of a DW project, and being able to attach user security information to the basic structures of a Multidimensional (MD) model. In this way, we would be able to generate this information in a semi or automatic way into a target platform and the final DW will better suits the user security requirements.

Using UML Packages for Designing Secure Data Warehouses

2006 ◽  
pp. 1024-1034 ◽  
Author(s):  
Rodolfo Villarroel ◽  
Emilio Soler ◽  
Eduardo Fernández-Medina ◽  
Juan Trujillo ◽  
Mario Piattini
Keyword(s):  
Data Warehouses ◽  
Secure Data

Developing secure data warehouses with a UML extension

2007 ◽  
Vol 32 (6) ◽  
pp. 826-856 ◽  
Author(s):  
Eduardo Fernández-Medina ◽  
Juan Trujillo ◽  
Rodolfo Villarroel ◽  
Mario Piattini
Keyword(s):  
Data Warehouses ◽  
Secure Data ◽  
Uml Extension

scholarly journals Balancing Privacy and Strategic Planning Needs: A Case Study in De-Identification of Patron Data

2017 ◽  
Vol 2 (1) ◽  
pp. 15
Author(s):  
Becky Yoose
Keyword(s):  
Data Analysis ◽  
Strategic Planning ◽  
Data Warehouse ◽  
Limited Resources ◽  
Evidence Based ◽  
Data Warehouses ◽  
Evidence Based Practices

The rise of evidence-based practices and assessment in libraries in recent years, combined with tying outcomes to future funding and resource allotments, has made libraries more reliant on patron data to determine how to allocate limited resources and funding. Libraries who want to use data for research and analysis but also wanting to protect patron privacy find themselves wondering how to balance these two priorities. This article explores The Seattle Public Library’s attempt to strike the balance between patron privacy and data analysis with the use of a data warehouse with de-identified patron data, as well as implications of data warehouses and de-identification as an option for other libraries.

Model-driven multidimensional modeling of secure data warehouses

2007 ◽  
Vol 16 (4) ◽  
pp. 374-389 ◽  
Author(s):  
Eduardo Fernández-Medina ◽  
Juan Trujillo ◽  
Mario Piattini
Keyword(s):  
Data Warehouses ◽  
Model Driven ◽  
Multidimensional Modeling ◽  
Secure Data

A Framework for Evaluating Design Methodologies for Big Data Warehouses

2018 ◽  
Vol 14 (1) ◽  
pp. 15-39 ◽  
Author(s):  
Francesco Di Tria ◽  
Ezio Lefons ◽  
Filippo Tangorra
Keyword(s):  
Big Data ◽  
Unstructured Data ◽  
Data Warehouses ◽  
Qualitative Information ◽  
Design Specifications ◽  
Set Up ◽  
Definition Of ◽  
Data Context

This article describes how the evaluation of modern data warehouses considers new solutions adopted for facing the radical changes caused by the necessity of reducing the storage volume, while increasing the velocity in multidimensional design and data elaboration, even in presence of unstructured data that are useful for providing qualitative information. The aim is to set up a framework for the evaluation of the physical and methodological characteristics of a data warehouse, realized by considering the factors that affect the data warehouse's lifecycle when taking into account the Big Data issues (Volume, Velocity, Variety, Value, and Veracity). The contribution is the definition of a set of criteria for classifying Big Data Warehouses on the basis of their methodological characteristics. Based on these criteria, the authors defined a set of metrics for measuring the quality of Big Data Warehouses in reference to the design specifications. They show through a case study how the proposed metrics are able to check the eligibility of methodologies falling in different classes in the Big Data context.

scholarly journals A Unified Conceptual Model for Data Warehouses

2021 ◽  
Vol 5 (5) ◽  
pp. 162-169
Author(s):  
Shreya Banerjee ◽  
Sourabh Bhaskar ◽  
Anirban Sarkar ◽  
Narayan C. Debnath
Keyword(s):  
Conceptual Model ◽  
Design Methodology ◽  
Data Modeling ◽  
Major Choice ◽  
Decision Makers ◽  
Systematic Design ◽  
Data Warehouses ◽  
Nosql Databases

These days, NoSQL (Not only SQL) databases are being used as a deployment tool for Data Warehouses (DW) due to its support for dynamic and scalable data modeling capabilities. Yet, decision-makers have faced several challenges to accept it as a major choice for implementation of their DW. The most significant one among those challenges is a lack of common conceptual model and a systematic design methodology for different NoSQL databases. The objective of this paper is to resolve these challenges by proposing an ontology based formal conceptual model for NoSQL based DWs. These proposed concepts are capable of realizing the cube concepts for visualization of multi-dimensional data in NoSQL based DW solutions. In this context, two strategies are specified, implemented and illustrated using a case study for devising of the proposed conceptual model.

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