Design and Implementation of Active Stream Data Warehouses

2021 ◽  
pp. 288-311
Author(s):  
Sandro Bimonte ◽  
Omar Boussaid ◽  
Michel Schneider ◽  
Fabien Ruelle
Keyword(s):  
Data Warehouse ◽  
Conceptual Modeling ◽  
Data Warehouses ◽  
Stream Data ◽  
Modeling Tools ◽  
Uml Profile ◽  
Classical Information ◽  
Design And Implementation ◽  
Eca Rules

In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the context of classical information and data warehouse systems, but they have not been investigated yet for stream data warehouses to deal with alert systems. Therefore, in this article, the authors introduce the notion of Active Stream Data Warehouse (ASDW) and this article proposes a UML profile for designing Active Stream Data Warehouses. Indeed, this article extends the ICSOLAP profile to take into account continuous and window OLAP queries. Moreover, this article studies the duality of the stream and OLAP decision-making process and the authors propose a set of ECA rules to automatically trigger OLAP operators. The UML profile is implemented in a new OLAP architecture, and it is validated using an environmental case study concerning the wind monitoring.

Design and Implementation of Active Stream Data Warehouses

2019 ◽  
Vol 15 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Sandro Bimonte ◽  
Omar Boussaid ◽  
Michel Schneider ◽  
Fabien Ruelle
Keyword(s):  
Data Warehouse ◽  
Conceptual Modeling ◽  
Decision Making Process ◽  
Data Warehouses ◽  
Stream Data ◽  
Modeling Tools ◽  
Uml Profile ◽  
Classical Information ◽  
Eca Rules

In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the context of classical information and data warehouse systems, but they have not been investigated yet for stream data warehouses to deal with alert systems. Therefore, in this article, the authors introduce the notion of Active Stream Data Warehouse (ASDW) and this article proposes a UML profile for designing Active Stream Data Warehouses. Indeed, this article extends the ICSOLAP profile to take into account continuous and window OLAP queries. Moreover, this article studies the duality of the stream and OLAP decision-making process and the authors propose a set of ECA rules to automatically trigger OLAP operators. The UML profile is implemented in a new OLAP architecture, and it is validated using an environmental case study concerning the wind monitoring.

Modeling and Specification of Collaborative Business Processes with a MDA Approach and a UML Profile

2010 ◽  
pp. 238-268
Author(s):  
Pablo David Villarreal ◽  
Enrique Salomone ◽  
Omar Chiotti
Keyword(s):  
Business Processes ◽  
Conceptual Modeling ◽  
Automatic Generation ◽  
Uml Profile ◽  
Analysis And Design ◽  
Model Driven ◽  
Collaborative Processes ◽  
Interaction Protocols ◽  
Business To Business

This chapter describes the application of MDA (model driven architecture) and UML for the modeling and specification of collaborative business processes, with the purpose of enabling enterprises to establish business-to-business collaborations. The proposed MDA approach provides the components and techniques required for the development of collaborative processes from their conceptual modeling to the specifications of these processes and the partners’ interfaces in a B2B standard. As part of this MDA approach, a UML profile is provided that extends the semantics of UML2 to support the analysis and design of collaborative processes. This UML profile is based on the use of interaction protocols to model collaborative processes. The application of this UML profile in a case study is presented. Also, an overview is provided about the automatic generation of B2B specifications from conceptual models of collaborative processes. In particular, the generation of B2B specifications based on ebXML is described.

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.

Conceptual Modeling for Data Warehouse and OLAP Applications

2011 ◽  
pp. 293-300
Author(s):  
Elzbieta Malinowski ◽  
Esteban Zimányi
Keyword(s):  
Data Warehouse ◽  
Conceptual Models ◽  
Conceptual Modeling ◽  
Relational Model ◽  
Data Warehouses ◽  
Logical Models ◽  
Levels Of Detail ◽  
On Line ◽  
State Of Affairs ◽  
Research Stage

The advantages of using conceptual models for database design are well known. In particular, they facilitate the communication between users and designers since they do not require the knowledge of specific features of the underlying implementation platform. Further, schemas developed using conceptual models can be mapped to different logical models, such as the relational, objectrelational, or object-oriented models, thus simplifying technological changes. Finally, the logical model is translated into a physical one according to the underlying implementation platform. Nevertheless, the domain of conceptual modeling for data warehouse applications is still at a research stage. The current state of affairs is that logical models are used for designing data warehouses, i.e., using star and snowflake schemas in the relational model. These schemas provide a multidimensional view of data where measures (e.g., quantity of products sold) are analyzed from different perspectives or dimensions (e.g., by product) and at different levels of detail with the help of hierarchies. On-line analytical processing (OLAP) systems allow users to perform automatic aggregations of measures while traversing hierarchies: the roll-up operation transforms detailed measures into aggregated values (e.g., daily into monthly sales) while the drill-down operation does the contrary. Star and snowflake schemas have several disadvantages, such as the inclusion of implementation details and the inadequacy of representing different kinds of hierarchies existing in real-world applications. In order to facilitate users to express their analysis needs, it is necessary to represent data requirements for data warehouses at the conceptual level. A conceptual multidimensional model should provide a graphical support (Rizzi, 2007) and allow representing facts, measures, dimensions, and different kinds of hierarchies.

Physical Modeling of Data Warehouses Using UML Component and Deployment Diagrams

2008 ◽  
pp. 591-621
Author(s):  
Serg Luján-Mora ◽  
Juan Trujillo
Keyword(s):  
Data Warehouse ◽  
Physical Modeling ◽  
Unified Modeling Language ◽  
Conceptual Modeling ◽  
Physical Nature ◽  
Physical Design ◽  
Design Decisions ◽  
Unified Modeling ◽  
Horizontal Partitioning

Several approaches have been proposed to model different aspects of a Data Warehouse (DW) during recent years, such as the modeling of a DW at the conceptual and logical level, the design of the ETL (Extraction, Transformation, Loading) processes, the derivation of the DW models from the enterprise data models, and customization of a DW schema. At the end of the design, a DW has to be deployed in a database environment, requiring many decisions of a physical nature. However, few efforts have been dedicated to the modeling of the physical design of a DW from the early stages of a DW project. In this article, we argue that some physical decisions can be taken from gathering main user requirements. In this article, we present physical modeling techniques for DWs using the component diagrams and deployment diagrams of the Unified Modeling Language (UML). Our approach allows the designer to anticipate important physical design decisions that may reduce the overall development time of a DW, such as replicating dimension tables, vertical and horizontal partitioning of a fact table, and the use of particular servers for certain ETL processes. Moreover, our approach allows the designer to cover all main design phases of DWs from the conceptual modeling phase to the final implementation. To illustrate our techniques, we show a case study that is implemented on top of a commercial DW management server.

Development of Data Warehouse Conceptual Models

2011 ◽  
pp. 1-23
Author(s):  
Laila Niedrite ◽  
Maris Solodovnikova Treimanis ◽  
Liga Grundmane
Keyword(s):  
Data Warehouse ◽  
Conceptual Models ◽  
Data Warehousing ◽  
Conceptual Modeling ◽  
Requirements Elicitation ◽  
Method Engineering ◽  
Data Warehouses ◽  
Engineering Approach ◽  
New Methods ◽  
Development Approach

There are many methods in the area of data warehousing to define requirements for the development of the most appropriate conceptual model of a data warehouse. There is no universal consensus about the best method, nor are there accepted standards for the conceptual modeling of data warehouses. Only few conceptual models have formally described methods how to get these models. Therefore, problems arise when in a particular data warehousing project, an appropriate development approach, and a corresponding method for the requirements elicitation, should be chosen and applied. Sometimes it is also necessary not only to use the existing methods, but also to provide new methods that are usable in particular development situations. It is necessary to represent these new methods formally, to ensure the appropriate usage of these methods in similar situations in the future. It is also necessary to define the contingency factors, which describe the situation where the method is usable.This chapter represents the usage of method engineering approach for the development of conceptual models of data warehouses. A set of contingency factors that determine the choice between the usage of an existing method and the necessity to develop a new one is defined. Three case studies are presented. Three new methods: userdriven, data-driven, and goal-driven are developed according to the situation in the particular projects and using the method engineering approach.

Modeling and Specification of Collaborative Business Processes with a MDS Approach and a UML Profile

2011 ◽  
pp. 13-44 ◽  
Author(s):  
Pablo David Villarreal ◽  
Enrique Salomone ◽  
Omar Chiotti
Keyword(s):  
Business Processes ◽  
Conceptual Modeling ◽  
Automatic Generation ◽  
Uml Profile ◽  
Analysis And Design ◽  
Model Driven ◽  
Collaborative Processes ◽  
Interaction Protocols ◽  
Business To Business

This chapter describes the application of MDA (Model-Driven Architecture) and UML for the modeling and specification of collaborative business processes, with the purpose of enabling enterprises to establish Business-to-Business collaborations. The proposed MDA approach provides the components and techniques required for the development of collaborative processes, from their conceptual modeling to the specifications of these processes and the partners’ interfaces in a B2B standard. As part of this MDA approach, a UML Profile is provided, which extends the semantics of UML 2 to support the analysis and design of collaborative processes. This UML Profile is based on the use of interaction protocols to model collaborative processes. The application of this UML Profile in a case study is presented. Also, an overview is provided about the automatic generation of B2B specifications from conceptual models of collaborative processes. In particular, the generation of B2B specifications based on ebXML is described.

A Grading Data Warehouse Approach to Measuring and Analyzing Learning Performance

2019 ◽  
pp. 102-126
Author(s):  
Michael Aram ◽  
Felix Mödritscher ◽  
Gustaf Neumann ◽  
Monika Andergassen
Keyword(s):  
Data Warehouse ◽  
Learning Performance ◽  
Record Management ◽  
Data Warehouses ◽  
Early Experiences ◽  
E Learning ◽  
Competency Based ◽  
Learning Platforms ◽  
Performance Issues

E-assessment comprises a variety of activities in and beyond the classroom. However, traditional e-learning platforms support only a part of assessment (e.g., individual and group assignments, the grading of such activities, and student record management). Typically, such platforms lack competency orientation, or face performance issues due to increasing application complexity and usage intensity. To overcome technical limitations and provide a basis for competency-based assessment, the authors present an analytics component that is inspired by data warehouses. The potential of this artifact is elaborated, and the improvements are evaluated through a case study about Learn@WU, the LMS of WU Vienna. Although the focus was competency-based aggregation of learning results, early experiences show performance increases for retrieving simple grades of 45% to 98%. Sample scenarios demonstrate how to define and calculate indicators along activity hierarchies and competency graphs to enable the measurement of learning performance along both generic indicators and competency-oriented assessment.

A Methodology for Building XML Data Warehouses

2008 ◽  
pp. 530-555
Author(s):  
Laura Irina Rusu ◽  
J. Wenny Rahayu ◽  
David Taniar
Keyword(s):  
Data Warehouse ◽  
Systematic Approach ◽  
Data Cleaning ◽  
The Other ◽  
Data Warehouses ◽  
Xml Data ◽  
Xml Database ◽  
Xml Documents

Developing a data warehouse for XML documents involves two major processes: one of creating it, by processing XML raw documents into a specified data warehouse repository; and the other of querying it, by applying techniques to better answer users’ queries. This paper focuses on the first part; that is identifying a systematic approach for building a data warehouse of XML documents, specifically for transferring data from an underlying XML database into a defined XML data warehouse. The proposed methodology on building XML data warehouses covers processes including data cleaning and integration, summarization, intermediate XML documents, and updating/linking existing documents and creating fact tables. In this paper, we also present a case study on how to put this methodology into practice. We utilise the XQuery technology in all of the above processes.

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