Building a Data Warehouse step by step

Data warehouses have been developed to answer the increasing demands of quality information required by the top managers and economic analysts of organizations. Their importance in now a day business area is unanimous recognized, being the foundation for developing business intelligence systems. Data warehouses offer support for decision-making process, allowing complex analyses which cannot be properly achieved from operational systems. This paper presents the ways in which a data warehouse may be developed and the stages of building it.data warehouse, data mart, data integration, database management system, OLAP, data mining

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Data Warehouse Design and Management: Theory and Practice

The need to store data and information permanently, for their reuse in later stages, is a very relevant problem in the modern world and now affects a large number of people and economic agents. The storage and subsequent use of data can indeed be a valuable source for decision making or to increase commercial activity. The next step to data storage is the efficient and effective use of information, particularly through the Business Intelligence, at whose base is just the implementation of a Data Warehouse. In the present paper we will analyze Data Warehouses with their theoretical models, and illustrate a practical implementation in a specific case study on a pharmaceutical distribution companyData warehouse, database, data model.

A Methodology for the Implementation and Maintenance Of a Data Warehouse

A methodology for the implementation and maintenance of a data warehouse is described. The data warehouse forms the basis for a marketing decision support system for use by a large surgical equipment manufacturer and requires integration of multiple sources of data external to the company. A prototype system is developed based upon the methodology. Each phase of the data warehouse implementation is discussed, including the data conversion process from raw data files to the prototype and production environments. Emphasis is placed upon the selection of suitable software tools for each process. The research approach employed is action research, in which the researcher participates with a client organization that exhibits the problems of interest to the investigator. The client organization is a large surgical equipment manufacturer, Ethicon Endo-Surgery

A Strategy for Reducing I/O and Improving Query Processing Time in an Oracle Data Warehouse Environment

In the current information age as the saying goes, time is money. For the modern information worker, decisions must often be made quickly. Every extra minute spent waiting for critical data could mean the difference between financial gain and financial ruin. Despite the importance of timely data retrieval, many organizations lack even a basic strategy for improving the performance of their data warehouse based reporting systems. This project explores the idea that a strategy making use of three database performance improvement techniques can reduce I/O (input/output operations) and improve query processing time in an information system designed for reporting. To demonstrate that these performance improvement goals can be achieved, queries were run on ordinary tables and then on tables utilizing the performance improvement techniques. The I/O statistics and processing times for the queries were compared to measure the amount of performance improvement. The measurements were also used to explain how these techniques may be more or less effective under certain circumstances, such as when a particular type of query is run. The collected I/O and time based measurements showed a varying degree of improvement for each technique based on the query used. A need to match the types of queries commonly run on the system to the performance improvement technique being implemented was found to be an important consideration. The results indicated that in a reporting environment these performance improvement techniques have the potential to reduce I/O and improve query performance