scholarly journals An MDA approach for developing secure OLAP applications: Metamodels and transformations

2015 ◽  
Vol 12 (2) ◽  
pp. 541-565 ◽  
Author(s):  
Carlos Blanco ◽  
Guzmán de ◽  
Eduardo Fernández-Medina ◽  
Juan Trujillo
Keyword(s):  
Decision Makers ◽  
Sql Server ◽  
Enterprise Information ◽  
Logical Models ◽  
Model Driven ◽  
Data Marts ◽  
On Line ◽  
Analytical Processing ◽  
Multidimensional Modelling ◽  
Secure Implementation

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).

A Conceptual Modeling Personalization Framework for OLAP

2012 ◽  
Vol 23 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Irene Garrigós ◽  
Jesús Pardillo ◽  
Jose-Norberto Mazón ◽  
Jose Zubcoff ◽  
Juan Trujillo ◽  
...  
Keyword(s):  
Conceptual Modeling ◽  
Decision Makers ◽  
User Characteristics ◽  
Processing Technologies ◽  
New Approach ◽  
Model Driven ◽  
On Line ◽  
Analytical Processing ◽  
And Behavior ◽  
Multidimensional Models

OLAP (On-line Analytical Processing) technologies rely on multidimensional models to provide decision makers with appropriate structures allowing them to intuitively analyze data. However, these multidimensional models may be potentially large, thus becoming too complex to be understood at a glance. Current approaches for OLAP design are focused on providing analysts with a single multidimensional schema derived from their previously stated information requirements, but this is not sufficient to lighten the complexity of the decision making process. To overcome this drawback, the authors propose personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behavior. In this paper, they present a new approach for personalizing OLAP systems at the conceptual level based on the underlying multidimensional model, a user model and a set of personalization rules. Transformations are defined by means of a model-driven strategy to assist in the process of obtaining the corresponding personalized OLAP schemas from these models.

CobWeb Multidimensional Model and Tag-Cloud Operators for OLAP of Documents

2018 ◽  
Vol 9 (2) ◽  
pp. 46-68
Author(s):  
Omar Khrouf ◽  
Kais Khrouf ◽  
Jamel Feki
Keyword(s):  
Decision Makers ◽  
Effective Management ◽  
Multidimensional Model ◽  
Tag Clouds ◽  
Xml Documents ◽  
Model Based ◽  
Tag Cloud ◽  
On Line ◽  
Analytical Processing ◽  
Software Prototype

There is an explosion in the amount of textual documents that have been generated and stored in recent years. Effective management of these documents is essential for better exploitation in decisional analyses. In this context, the authors propose their CobWeb multidimensional model based on standard facets and dedicated to the OLAP (on-line analytical processing) of XML documents; it aims to provide decision makers with facilities for expressing their analytical queries. Secondly, they suggest new visualization operators for OLAP query results by introducing the concept of Tag clouds as a means to help decision-makers to display OLAP results in an intuitive format and focus on main concepts. The authors have developed a software prototype called MQF (Multidimensional Query based on Facets) to support their proposals and then tested it on documents from the PubMed collection.

Application of OLAP Technology in the Environment of Electronic Demography

2021 ◽  
Vol 27 (10) ◽  
pp. 542-549
Author(s):  
G. Ch. Nabibayova ◽  
Keyword(s):  
Decision Makers ◽  
Practical Application ◽  
Demographic Research ◽  
Computing Model ◽  
Interdisciplinary Field ◽  
Parallel Data ◽  
Data Marts ◽  
Data Volume ◽  
Analytical Processing ◽  
High Level

The article proposes an approach to the development of an electronic demographic decision support system using technologies of Data Warehouse (DW) and Interactive Analytical Processing OLAP. This makes it possible to conduct high-level demographic research and provide support to decision-makers in demographic sphere. The article notes that demography is an interdisciplinary field of research and is defined as a complex science. Each industry of demography has many indicators. A sample list of these indicators is presented. The main characteristics of the DW, which should be taken into account when developing its architecture, are stated. Among these characteristics, one can find the main defining characteristics of Big Data — volume, velocity, variety, veracity, variability, visualization, value etc. For a more rational and efficient use of a large amount of information, taking into account its constant increase, to ensure the speed of execution of requests for a given system, it is proposed to use a Bus of Interconnected Data Marts (DM) as an architecture of DW. One of the advantages of using DM is that their use assumes distributed parallel data processing. This architecture allows for much faster results generation. It is based on the MapReduce distributed computing model and the Hadoop project. In addition, to effectively use large amounts of data, it is also proposed to use OLAP operations such as roll-up and drill-down, as well as fuzzy set theory, based on the technique of computing with words. The article also shows the practical application of interconnected DM. An OLAP cube is built on the basis of these DM. OLAP operations provide the ability to view cubes in different slices and provide aggregate data.

Enhancing the Diamond Document Warehouse Model

2020 ◽  
Vol 16 (4) ◽  
pp. 1-25
Author(s):  
Maha Azabou ◽  
Ameen Banjar ◽  
Jamel Omar Feki
Keyword(s):  
Data Warehouse ◽  
Decision Makers ◽  
Main Concern ◽  
Multidimensional Model ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

The data warehouse community has paid particular attention to the document warehouse (DocW) paradigm during the last two decades. However, some important issues related to the semantics are still pending and therefore need a deep research investigation. Indeed, the semantic exploitation of the DocW is not yet mature despite it representing a main concern for decision-makers. This paper aims to enhancing the multidimensional model called Diamond Document Warehouse Model with semantics aspects; in particular, it suggests semantic OLAP (on-line analytical processing) operators for querying the DocW.

scholarly journals Electronic demography decision making system

2020 ◽  
pp. 228-236
Author(s):  
G.Ch. Nabibekova ◽  
Keyword(s):  
Data Warehouse ◽  
Decision Makers ◽  
Practical Application ◽  
Data Marts ◽  
Decision Making System ◽  
Demographic Processes ◽  
Analytical Processing ◽  
Using Data ◽  
High Level ◽  
Bus Architecture

The article suggests an approach to the development of an electronic demographic decision support system using data warehouse and interactive analytical processing OLAP. This makes it possible to conduct research on demographic processes at a high level and to support decision makers in the field of demography. Due to the presence of many types of demography and a large number of indicators, proposed in the article, a Data Mart Bus Architecture with Linked Dimensional Data Marts is proposed as a Data Warehouse architecture. The article also shows the practical application of this approach using two Data Marts as an example. Based on these Data Marts, OLAP-cubes are built. OLAP operations provide the ability to view cubes in various slices, as well as provide aggregate data.

scholarly journals On-line Analytical Processing (OLAP) Operation for Outpatient Healthcare

2021 ◽  
pp. 225-231
Author(s):  
Talib M. J. Al Taleb ◽  
Sami Hasan ◽  
Yaqoob Yousif Mahd
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
Decision Makers ◽  
Data Repository ◽  
Managerial Decision ◽  
High Quality Information ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
Different Sources

This paper presents an architecture for the data warehouse of outpatient healthcare (DWOP) as a data repository collects data from two different sources (Databases of outpatient healthcare and Excel files from hospitals) and provides storage, functionality and responsiveness to queries to meet decision makers requirements.Successfully supporting managerial decision-making is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. “On-Line Analytical Processing (OLAP) is utilized for decision support to get interesting information” from the data warehouse with a rapid execution time. OLAP is considered one of Business Intelligence tools.

scholarly journals Study of Indoor Radon Using Data Mining Models Based on OLAP Cubes

2020 ◽  
pp. 53-61
Author(s):  
Javier García-Tobar
Keyword(s):  
Data Mining ◽  
Indoor Radon ◽  
Residential Building ◽  
Sql Server ◽  
Radon Measurement ◽  
Measurement Campaign ◽  
On Line ◽  
Analytical Processing ◽  
Using Data ◽  
Radon Measurements

This research has focused on a radon measurement campaign that was carried out in two dwellings in a residential building located in Madrid. A new methodology has been used in this field, such as the use of cubes based on On-Line Analytical Processing in SQL Server Analysis Services. The application of this methodology can be of particular interest in analysing thousands of radon measurements and complementary variables, which are easily obtained in any radon measurement campaign.

Evolutionary Intelligent Data Warehousing Approach to Knowledge Discovery Systems: Dynamic Cubing

2019 ◽  
Vol 13 ◽  
Author(s):  
Harkiran Kaur ◽  
Kawaljeet Singh ◽  
Tejinder Kaur
Keyword(s):  
Knowledge Discovery ◽  
Data Warehouse ◽  
Business Intelligence ◽  
End Users ◽  
Processing Stage ◽  
Information Update ◽  
On Line ◽  
Analytical Processing ◽  
Warehouse Operations ◽  
Made In

Background: Numerous E – Migrants databases assist the migrants to locate their peers in various countries; hence contributing largely in communication of migrants, staying overseas. Presently, these traditional E – Migrants databases face the issues of non – scalability, difficult search mechanisms and burdensome information update routines. Furthermore, analysis of migrants’ profiles in these databases has remained unhandled till date and hence do not generate any knowledge. Objective: To design and develop an efficient and multidimensional knowledge discovery framework for E - Migrants databases. Method: In the proposed technique, results of complex calculations related to most probable On-Line Analytical Processing operations required by end users, are stored in the form of Decision Trees, at the pre- processing stage of data analysis. While browsing the Cube, these pre-computed results are called; thus offering Dynamic Cubing feature to end users at runtime. This data-tuning step reduces the query processing time and increases efficiency of required data warehouse operations. Results: Experiments conducted with Data Warehouse of around 1000 migrants’ profiles confirm the knowledge discovery power of this proposal. Using the proposed methodology, authors have designed a framework efficient enough to incorporate the amendments made in the E – Migrants Data Warehouse systems on regular intervals, which was totally missing in the traditional E – Migrants databases. Conclusion: The proposed methodology facilitate migrants to generate dynamic knowledge and visualize it in the form of dynamic cubes. Applying Business Intelligence mechanisms, blending it with tuned OLAP operations, the authors have managed to transform traditional datasets into intelligent migrants Data Warehouse.

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