Data Warehouse Architectures Research Articles

Flexible Data Warehouse Parameters: Toward Building an Integrated Architecture

Clinical databases have gathered a huge amount of information about patients and their medical conditions. Relationships and patterns within this data could provide new medical knowledge. Thus it is a difficult task focusing to model a data warehouse, very often, into internal structures and implementation applications. The aim of is project is to find the parameters of medical data warehouse which will be able to construct a flexible framework by analyze the approaches of data warehouse architectures and compare them regarding the cost and integrity. The proposed parameters may assist in achieving continual access to the common data warehouse. The important consideration, however, is that the clinical data record should contain not only longitudinal health summary information but also be used for business intelligence tool such as data mining and OLAP

Taxonomy of Different Data Warehouse Architectures & Need for Optimized Data Warehouse

Different architectures have been proposed for Data Warehouse. This paper gives a survey of the various architecture techniques used and justifies why there is still a need for optimized data warehouse architecture which overcomes the limitations or challenges of the existing techniques. Survey includes OLAM architecture (combination of Data mining and OLAP), complex Data Warehouse architecture, Real Time storage Architecture, Data Ware House Architecture through view point of information system and Model Driven approach for Data Warehouse. Ultimate goal of this paper is to propose an architecture which is fault tolerant, has less resource consumption and user friendly.

A New Architecture for Large Data Warehouse

Data warehouse is playing a more and more important role in company’s decision making; it is the basis for a typical business intelligence solution. The paper points out the reasons why data warehouse projects failed and by analyzing the current data warehouse architectures, as well as technologies used in industry, a new data warehouse architecture is proposed which has many advantages over current ones, for example, it is extensible, reusable, flexible and with high performance and lower cost.

Representation of conceptual ETL designs in natural language using Semantic Web technology

Extract-Transform-Load (ETL) processes constitute the back stage of Data Warehouse architectures. Several studies characterize the ETL design as a time-consuming and error-prone procedure. A critical phase in the ETL lifecycle involves the early communications and design steps that aim at producing a conceptual ETL design. Various research approaches have dealt with the conceptual modeling of ETL processes, but all share two inconveniences: they require intensive human effort from the designers to create them, as well as technical knowledge from the business people to understand them. In this paper, we focus on the second aspect and provide a method for the representation of a conceptual ETL design as a narrative, which is the most natural means of communication and does not require particular technical skills or familiarity with any specific model. Specifically, this work builds upon previously proposed techniques that automate the conceptual design by leveraging Semantic Web technology. The key idea is to map the involved data stores, either source or target, to a domain ontology and then, to use a reasoner for producing the ETL design. We discuss how linguistic techniques can be used for the establishment of a common application vocabulary. We present a flexible and customizable template-based mechanism for the representation of the ETL design as a narrative. Finally, we discuss issues related to the production of meaningful reports and we provide implementation details.