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

The design, development and deployment of a data warehouse (DW) is a complex, time consuming and prone to fail task. This is mainly due to the different aspects taking part in a DW architecture such as data sources, processes responsible for Extracting, Transforming and Loading (ETL) data into the DW, the modeling of the DW itself, specifying data marts from the data warehouse or designing end user tools. In the last years, different models, methods and techniques have been proposed to provide partial solutions to cover the different aspects of a data warehouse. Nevertheless, none of these proposals addresses the whole development process of a data warehouse in an integrated and coherent manner providing the same notation for the modeling of the different parts of a DW. In this paper, we propose 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. We use the extension mechanisms (stereotypes, tagged values and constraints) provided by the UML and we properly extend it in order to accurately model the different parts of a data warehouse (such as the modeling of the data sources, ETL processes or the modeling of the DW itself) by using the same notation. To the best of our knowledge, our proposal provides a seamless method for developing data warehouses. Finally, we apply our approach to a case study to show its benefit.This work has been partially supported by the METASIGN project (TIN2004-OO779) from the Spanish Ministry of Education and Science, by the DADASMECA project (GV05/220) from the Valencia Government, and by the DADS (PBC-05-QI 2-2) project from the Regional Science arid Technology Ministry of CastiIla-La Mancha (Spain)

Heterogeneous Relational Databases for a Grid-enabled Analysis Environment

Grid based systems require a database access mechanism that can provide seamless homogeneous access to the requested data through a virtual data access system, i.e. a system which can take care of tracking the data that is stored in geographically distributed heterogeneous databases. This system should provide an integrated view of the data that is stored in the different repositories by using a virtual data access mechanism, i.e. a mechanism which can hide the heterogeneity of the backend databases from the client applications. This paper focuses on accessing data stored in disparate relational databases through a web service interface, and exploits the features of a Data Warehouse and Data Marts. We present a middleware that enables applications to access data stored in geographically distributed relational databases without being aware of their physical locations and underlying schema. A web service interface is provided to enable applications to access this middleware in a language and platform independent way. A prototype implementation was created based on Clarens [4], Unity [7] and POOL [8]. This ability to access the data stored in the distributed relational databases transparently is likely to be a very powerful one for Grid users, especially the scientific community wishing to collate and analyze data distributed over the Grid

Warehouse commodity classification from fundamental principles. Part II: Flame heights and flame spread

In warehouse storage applications, it is important to classify the burning behavior of commodities and rank them according to their material flammability for early fire detection and suppression operations. In this study, a preliminary approach towards commodity classification is presented that models the early stage of large-scale warehouse fires by decoupling the problem into separate processes of heat and mass transfer. Two existing nondimensional parameters are used to represent the physical phenomena at the large-scale: a mass transfer number that directly incorporates the material properties of a fuel, and the soot yield of the fuel that controls the radiation observed in the large-scale. To facilitate modeling, a mass transfer number (or B-number) was experimentally obtained using mass-loss (burning rate) measurements from bench-scale tests, following from a procedure that was developed in Part I of this paper. Two fuels are considered: corrugated cardboard and polystyrene. Corrugated cardboard provides a source of flaming combustion in a warehouse and is usually the first item to ignite and sustain flame spread. Polystyrene is typically used as the most hazardous product in large-scale fire testing. The nondimensional mass transfer number was then used to model in-rack flame heights on 6.19.1 m (2030 ft) stacks of 'C' flute corrugated cardboard boxes on rack-storage during the initial period of flame spread (involving flame spread over the corrugated cardboard face only). Good agreement was observed between the model and large-scale experiments during the initial stages of fire growth, and a comparison to previous correlations for in-rack flame heights is included. © 2011 Elsevier Ltd. All rights reserved

Warehouse commodity classification from fundamental principles. Part I: Commodity & burning rates

An experimental study was conducted to investigate the burning behavior of an individual Group A plastic commodity over time. The objective of the study was to evaluate the use of a nondimensional parameter to describe the time-varying burning rate of a fuel in complex geometries. The nondimensional approach chosen to characterize burning behavior over time involved comparison of chemical energy released during the combustion process with the energy required to vaporize the fuel, measured by a B-number. The mixed nature of the commodity and its package, involving polystyrene and corrugated cardboard, produced three distinct stages of combustion that were qualitatively repeatable. The results of four tests provided flame heights, mass-loss rates and heat fluxes that were used to develop a phenomenological description of the burning behavior of a plastic commodity. Three distinct stages of combustion were identified. Time-dependent and time-averaged B-numbers were evaluated from mass-loss rate data using assumptions including a correlation for turbulent convective heat transfer. The resultant modified B-numbers extracted from test data incorporated the burning behavior of constituent materials, and a variation in behavior was observed as materials participating in the combustion process varied. Variations between the four tests make quantitative values for each stage of burning useful only for comparison, as errors were high. Methods to extract the B-number with a higher degree of accuracy and future use of the results to improve commodity classification for better assessment of fire danger are discussed. © 2011 Elsevier Ltd. All rights reserved

The Dag-Brucken ASRS Case Study

In 1996 an agreement was made between a well-known beverage manufacturer, Super-Cola Taiwan, (SCT) and a small Australian electrical engineering company, Dag-Brücken ASRS Pty Ltd, (DB), to provide an automated storage and retrieval system (ASRS) facility as part of SCT’s production facilities in Asia. Recognising the potential of their innovative and technically advanced design, DB was awarded a State Premiers Export Award and was a finalist in that year’s National Export Awards. The case tracks the development and subsequent implementation of the SCT ASRS project, setting out to highlight how the lack of appropriate IT development processes contributed to the ultimate failure of the project and the subsequent winding up of DB only one year after being honoured with these prestigious awards. The case provides compelling evidence of the types of project management incompetency that, from the literature, appears to contribute to the high failure rate in IT projects. For confidentiality reasons, the names of the principal parties are changed, but the case covers actual events documented by one of the project team members as part of his postgraduate studies, providing an example of the special mode of evidence collection that Yin (1994) calls ‘participant-observation’

Web-enabled Data Warehouse and Data Webhouse

In this paper, our objectives are to understanding what data warehouse means examine the reasons for doing so, appreciate the implications of the convergence of Web technologies and those of the data warehouse and examine the steps for building a Web-enabled data warehouse. The web revolution has propelled the data warehouse out onto the main stage, because in many situations the data warehouse must be the engine that controls or analysis the web experience. In order to step up to this new responsibility, the data warehouse must adjust. The nature of the data warehouse needs to be somewhat different. As a result, our data warehouses are becoming data webhouses. The data warehouse is becoming the infrastructure that supports customer relationship management (CRM). And the data warehouse is being asked to make the customer clickstream available for analysis. This rebirth of data warehousing architecture is called the data webhouse.data warehouse, web-enabled, data mart, Internet, intranet, extranet

On the Economic Value and Price-Responsiveness of Ramp-Constrained Storage

The primary concerns of this paper are twofold: to understand the economic value of storage in the presence of ramp constraints and exogenous electricity prices, and to understand the implications of the associated optimal storage management policy on qualitative and quantitative characteristics of storage response to real-time prices. We present an analytic characterization of the optimal policy, along with the associated finite-horizon time-averaged value of storage. We also derive an analytical upperbound on the infinite-horizon time-averaged value of storage. This bound is valid for any achievable realization of prices when the support of the distribution is fixed, and highlights the dependence of the value of storage on ramp constraints and storage capacity. While the value of storage is a non-decreasing function of price volatility, due to the finite ramp rate, the value of storage saturates quickly as the capacity increases, regardless of volatility. To study the implications of the optimal policy, we first present computational experiments that suggest that optimal utilization of storage can, in expectation, induce a considerable amount of price elasticity near the average price, but little or no elasticity far from it. We then present a computational framework for understanding the behavior of storage as a function of price and the amount of stored energy, and for characterization of the buy/sell phase transition region in the price-state plane. Finally, we study the impact of market-based operation of storage on the required reserves, and show that the reserves may need to be expanded to accommodate market-based storage