Maintenance Modification Algorithms and its Implementation on object oriented data warehouse

A data warehouse (DW) is a database used for reporting Paper describes Modification Algorithm and implementation on Object Oriented Data Warehousing. A Data Warehouse collects information and data from source data bases to support analytical processing of decision support functions and acts as an information provider. In initial research data warehouses focused on relational data model. In this paper concept of object oriented data warehouse is introduced modification maintenance algorithms and its implementation to maintained consistency between data warehouse and source data base

Modélisation et manipulation de données historisées et archivées dans un entrepôt orienté objet

National audienceThis paper deals with temporal and archive object-oriented data warehouse modelling and querying. In a first step, we define a data model describing warehouses as central repositories of complex and temporal data extracted from one information source. The model is based on the concepts of warehouse object and environment. A warehouse object is composed of one current state, several past states (modelling value changes) and several archive states (summarising some value changes). An environment defines temporal parts in a warehouse schema according to a relevant granularity (attribute, class or graph). In a second step, we provide a query algebra dedicated to data warehouses. This algebra, which is based on common object algebras, integrates temporal operators and operators for querying object states. An other important contribution concerns dedicated operators allowing users to transform warehouse objects in temporal series as well as operators facilitating analytical treatments

Modélisation et extraction de données pour un entrepôt objet

National audienceThis paper describes an object-oriented model for designing complex and time-variant data warehouse data. The main contribution is the warehouse class concept, which extends the class concept by temporal and archive filters as well as a mapping function. Filters allow the keeping of relevant data changes whereas the mapping function defines the warehouse class schema from a global data source schema. The approach take into account static properties as well as dynamic properties. The behaviour extraction is based on the use-matrix concept

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An approach to organizing universal programming environment, intended to form the departmental document-oriented data warehouse of the educational institution, is offered in the article. Available possibility of individual design of business logic that is generally characteristic for educational activities. The concept of specialized warehouse of semistructured data is based on the logical model “object-attribute-value”, which allows not only to store electronic documents with a different sets of attributes, but also to maintain the dynamics of these sets.-

Design of a Multidimensional Model Using Object Oriented Features in UML

A data warehouse is a single repository of data which includes data generated from various operational systems. Conceptual modeling is an important concept in the successful design of a data warehouse. The Unified Modeling Language (UML) has become a standard for object modeling during analysis and design steps of software system development. The paper proposes an object oriented approach to model the process of data warehouse design. The hierarchies of each data element can be explicitly defined, thus highlighting the data granularity. We propose a UML multidimensional model using various data sources based on UML schemas. We present a conceptual-level integration framework on diverse UML data sources on which OLAP operations can be performed. Our integration framework takes into account the benefits of UML (its concepts, relationships and extended features) which is more close to the real world and can model even the complex problems easily and accurately. Two steps are involved in our integration framework. The first one is to convert UML schemas into UML class diagrams. The second is to build a multidimensional model from the UML class diagrams. The white-paper focuses on the transformations used in the second step. We describe how to represent a multidimensional model using a UML star or snowflake diagram with the help of a case study. To the best of our knowledge, we are the first people to represent a UML snowflake diagram that integrates heterogeneous UML data sources