Automatic generation of data merging program codes.

Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level. Our formalized transformation described using ATL (ATLAS Transformation Language) enables automatic generation of PL/SQL packages to execute data merging in commercial ETL tools. With this approach data warehouse engineers can be relieved from the burden of repetitive complex script coding and the pain of maintaining consistency of design and implementation

Automatic generation of data merging program codes

Data merging is an essential part of ETL (Extract-Transform-Load) processes to build a data warehouse system. To avoid rewheeling merging techniques, we propose a Data Merging Meta-model (DMM) and its transformation into executable program codes in the manner of model driven engineering. DMM allows defining relationships of different model entities and their merging types in conceptual level. Our formalized transformation described using ATL (ATLAS Transformation Language) enables automatic generation of PL/SQL packages to execute data merging in commercial ETL tools. With this approach data warehouse engineers can be relieved from the burden of repetitive complex script coding and the pain of maintaining consistency of design and implementation

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

XML content warehousing: Improving sociological studies of mailing lists and web data

In this paper, we present the guidelines for an XML-based approach for the sociological study of Web data such as the analysis of mailing lists or databases available online. The use of an XML warehouse is a flexible solution for storing and processing this kind of data. We propose an implemented solution and show possible applications with our case study of profiles of experts involved in W3C standard-setting activity. We illustrate the sociological use of semi-structured databases by presenting our XML Schema for mailing-list warehousing. An XML Schema allows many adjunctions or crossings of data sources, without modifying existing data sets, while allowing possible structural evolution. We also show that the existence of hidden data implies increased complexity for traditional SQL users. XML content warehousing allows altogether exhaustive warehousing and recursive queries through contents, with far less dependence on the initial storage. We finally present the possibility of exporting the data stored in the warehouse to commonly-used advanced software devoted to sociological analysis

SODA: Generating SQL for Business Users

The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated. This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses.Comment: VLDB201

Radio frequency identification (RFID) technologies for locating warehouse resources: A conceptual framework

Copyright @ 2012 Information Technology SocietyIn the supply chain, a warehouse is a crucial component for linking all chain parties. It is necessary to track the real time resource location and status to support warehouse operations effectively. Therefore, RFID technology has been adopted to facilitate the collection and sharing of data in a warehouse environment. However, an essential decision should be made on the type of RFID tags the warehouse managers should adopt, because it is very important to implement RFID tags that work in warehouse environment. As a result, the warehouse resources will be easily tracked and accurately located which will improve the visibility of warehouse operations, enhance the productivity and reduce the operation costs of the warehouse. Therefore, it is crucial to evaluate the reading performance of all types of RFID tags in a warehouse environment in order to choose the most appropriate RFID tags which will enhance the operational efficiency of a warehouse. Reading performance of active and passive RFID tags have been evaluated before while, semi-passive RFID tag, which is battery-assisted with greater sensitivity than passive tags and cheaper than active tags, has not been examined yet in a warehouse environment. This research is in- progress research and it seeks to (i) provide a general overview of the existing real-time data management techniques in tracking warehouse resources location, (ii) provide an overall conceptual framework that can help warehouse managers to choose the best RFID technologies for a warehouse environment, (iii) Finally, the paper submits an experiment design for evaluating the reading performance of semi-passive RFID tags in a warehouse environment