software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. In this paper, we focus on the problem of the definition of ETL activities and provide formal foundations for their conceptual representation. The proposed conceptual model is (a) customized for the tracing of inter-attribute relationships and the respective ETL activities in the early stages of a data warehouse project; (b) enriched with a 'palette' of a set of frequently used ETL activities, like the assignment of surrogate keys, the check for null values, etc; and (c) constructed in a customizable and extensible manner, so that the designer can enrich it with his own re-occurring patterns for ETL activities.

Based on a subset of the Unified Modeling Language, the authors ’ objectoriented approach to building data warehouses frees conceptual design from implementation issues. Most developers agree that data warehouse, multidimensional database (MDB), and online analytical processing (OLAP) applications emphasize multidimensional modeling, which offers two benefits. First, the multidimensional model closely parallels how data analyzers think and, therefore, helps users understand data. Second, this approach helps predict what final users want to do, thereby facilitating performance improvements. Developers have proposed various approaches for the conceptual design of multidimensional systems.

The words On-Line Analytical Processing (OLAP) bring together a set of tools, that use multidimensional modeling in the extraction of information from the Data Warehouse. Lately, a lot of work has been devoted to modeling the multidimensional space. The aim of this paper is twofold. On one hand, it compiles and classifies most of that work. On the other hand, it allows to compare the different terminology used by each author, by placing all the terms in a common framework.

"On-Line Analytical Processing" tools are used to extract information from the "Data Warehouse" in order to help in the decision making process. These tools are based on multidimensional concepts, i.e. facts and dimensions. In this paper we study the meaning of facts, and the dependencies in multidimensional data. This study is used to find relationships between cubes (in an Object-Oriented framework) and explain navigation operations.

Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. The design, development and deployment of ETL processes, which is currently, performed in an ad-hoc, in house fashion, needs modeling, design and methodological foundations. Unfortunately, the research community has a lot of work to do to confront this shortcoming. Our research explores a coherent framework for the conceptual, the logical, and the physical design of ETL processes. We delve into the modeling of ETL activities and provide a conceptual and a logical abstraction for the representation of these processes. Moreover, we focus on the optimization of the ETL processes, in order to minimize the execution time of an ETL process. 1.

Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization and insertion into a data warehouse. In this paper, we propose a methodology for the earliest stages of the data warehouse design, with the goal of tracing the analysis of the structure and content of the existing data sources and their intentional mapping to the common conceptual data warehouse model. The methodology comprises a set of steps that can be summarized as follows: (a) identification of the proper data stores; (b) candidates and active candidates for the involved data stores; (c) attribute mapping between the providers and the consumers, and (d) annotation of the diagram with runtime constraints.

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