Data Mapping Diagrams for Data Warehouse Design with UML

  title={Data Mapping Diagrams for Data Warehouse Design with UML},
  author={Sergio Luj{\'a}n-Mora and Panos Vassiliadis and Juan Trujillo},
  booktitle={International Conference on Conceptual Modeling},
In Data Warehouse (DW) scenarios, ETL (Extraction, Transformation, Loading) processes are responsible for the extraction of data from heterogeneous operational data sources, their transformation (conversion, cleaning, normalization, etc.) and their loading into the DW. In this paper, we present a framework for the design of the DW back-stage (and the respective ETL processes) based on the key observation that this task fundamentally involves dealing with the specificities of information at very… 

Applying the UML and the Unified Process to the Design of Data Warehouses

A data warehouse development method, based on the Unified Modeling Language (UML) and the Unified Process (UP), which addresses the design and development of both the data warehouse back-stage and front-end and provides a seamless method for developing data warehouses.

Physical Modeling of Data Warehouses Using UML Component and Deployment Diagrams: Design and Implementation Issues

This article argues that some physical decisions can be taken from gathering main user requirements and presents physical modeling techniques for DWs using the component diagrams and deployment diagrams of the Unified Modeling Language (UML).

Automatic generation of ETL processes from conceptual models

This paper defines an approach for the automatic code generation of ETL processes in DW with MDA (Model Driven Architecture) by formally defining a set of QVT (Query, View, Transformation) transformations.

A semantic approach to ETL technologies

An Approach for Designing, Modeling and Realizing ETL Processes Based on Unified Views Model

A new architecture based on Unified Views Model (UVM) for ETL processes is proposed, in which Unified view layer is added between source data level and DWs level, and an ETL tool based on UVM (UVETL) is presented.

Ontology-Driven Conceptual Design of ETL Processes Using Graph Transformations

This paper proposes a customizable and extensible ontology-driven approach for the conceptual design of ETL processes, using a graph-based representation used as a conceptual model for the source and target data stores and presents a method for devising flows ofETL operations by means of graph transformations.

Physical modeling of data warehouses using UML

The 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, the use of particular servers for certain ETL processes and so on.

An approach to conceptual modelling of ETL processes

  • Sasa DuporV. Jovanovic
  • Computer Science
    2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)
  • 2014
A new conceptual model based on the visualization of data flow showing transformations of records accompanied with attribute transformations is proposed, which can be used for development of an ETL process, maintenance/optimization and redesign of a process due to new business requirements and database schema changes.



A UML Based Approach for Modeling ETL Processes in Data Warehouses

This paper provides the necessary mechanisms for an easy and quick specification of the common operations defined in these ETL processes such as, the integration of different data sources, the transformation between source and target attributes, the generation of surrogate keys and so on.

Conceptual modeling for ETL processes

The proposed conceptual model is customized for the tracing of inter-attribute relationships and the respective ETL activities in the early stages of a data warehouse project and constructed in a customizable and extensible manner, so that the designer can enrich it with his own re-occurring patterns forETL activities.

Modeling ETL activities as graphs

This paper focuses on the logical design of the ETL scenario of a data warehouse, which is based on a formal logical model that includes the data stores, activities and their constituent parts as a graph, which it is called the Architecture Graph.

Extending the UML for Multidimensional Modeling

This paper presents an extension of the Unified Modeling Language (UML), by means of stereotypes, to elegantly represent main structural and dynamic MD properties at the conceptual level, made use of the Object Constraint Language (OCL) to specify the constraints attached to the defined stereotypes, thereby avoiding an arbitrary use of these stereotypes.

Operators and Classification for Data Mapping in Semantic Integration

This paper discusses issues related to the data mapping phase of the integration of outsourced data, and introduces a set of mapping operators for both entities and attributes.

Data Warehouse Scenarios for Model Management

The case study illustrates the value of model management as a methodology for approaching meta-data related problems and helps clarify the required semantics of key operations.

Data Modeling in UML and ORM: A Comparison

The relative strengths and weaknesses of ORM and UML for data modeling are examined, and how models in one notation can be translated into the other are indicated.

A vision for management of complex models

This work proposes to make database systems easier to use for these applications by making "model" and "model mapping" first-class objects with special operations that simplify their use, and produces a sketch of a proposed data model.

Multidimensional Modeling with UML Package Diagrams

This paper presents the development of multidimensional (MD) models for data warehouses (DW) using UML package diagrams, and provides a UML extension by means of stereotypes of the particular package items the authors use.

Data integration: a theoretical perspective

The tutorial is focused on some of the theoretical issues that are relevant for data integration: modeling a data integration application, processing queries in data integration, dealing with inconsistent data sources, and reasoning on queries.